EA036572B1 - Method to detect incremental oil production arising from a low salinity waterflood - Google Patents

Abstract

Described herein is a method for detecting incremental oil production from an oil-bearing reservoir (3) that is penetrated by at least one injection well (10) and at least one production well (1a-d), the process comprising taking a baseline sample of the oil and analyzing the baseline sample of oil to establish a baseline compositional signature for the oxygen-containing organic compounds in the oil; commencing a low salinity waterflood by injecting a low salinity water into the reservoir from the injection well; recovering oil from the production well; taking post-flood samples of the oil produced from the production well over time; analyzing the post-flood samples of oil to establish post-flood compositional signatures for the oxygen-containing organic compounds in the oil; and identifying a difference between one or more of the post-flood compositional signatures for the oxygen-containing organic compounds in the oil and the baseline compositional signature for the oxygen-containing organic compounds in the oil that is characteristic of incremental oil released by the low salinity waterflood.

Description

Technology area

The present invention relates to the monitoring of low salinity waterflooding in an oil reservoir.

State of the art

In the first stage of production of hydrocarbons from the formation (called primary production), hydrocarbon fluids are pushed by the natural pressure of the formation towards the production well, where these fluids can flow out or pumped out to surface production equipment. Primary production can continue as long as the formation pressure exceeds the saturation pressure of the formation oil. If the reservoir pressure drops below the bubble point pressure of the reservoir oil, additional reservoir pressure is required to prevent gas from escaping from solution in the reservoir. Typically, the reservoir pressure is sufficient to produce only about 10-20% of all oil in the underground oil reservoir. Accordingly, re-oil recovery technology is used to recover oil from formations from which hydrocarbon fluids no longer naturally flow out.

One of the most effective and widely used secondary oil recovery methods is oil field flooding. Water is usually injected under pressure into the porous formation through an injection well to maintain reservoir pressure and propels the oil through the porous formation to the production wells. The water used in waterflooding can be highly saline water, such as seawater, estuary water, aquifer water, or process water (water separated from oil and gas in production equipment).

The water used in waterflooding can also be low salinity water. Thus, in the international patent application WO 2008/029124 it is shown that the oil recovery of a reservoir containing oil-bearing sandstone increases (in comparison with the injection of high salinity water) when the total dissolved solids content (TDS) in the injected water is from 200 to 12000 vol. ppm, and the ratio of the content of multivalent cations in the injected water to the same ratio in the relict water contained in the sandstone formation is less than 1.

An increase in the amount of oil that can be recovered and sandstone formations due to a decrease in the salinity of the injected water has been demonstrated on a laboratory scale (Tang, G.-Q., And Morrow, NR, Influence of brine composition and fines migration on crude / brine / rock interactions and oil recovery, Journal of Petroleum Science and Engineering, 1990), well tests using a single marker (McGuire, PL, Chatham, JR, Paskvan, FK, Sommer, DM, and Carini, FH, Low Salinity Oil Recovery: An Exciting New EOR Opportunity for Alaska's North Slope, SPE 93903, 2005) and full-scale field trials (Seccomb, J., Lager, G., Jhavery, B., Buikema, T., Bassler, S., Denis, J., Webb, K ., Cockin, A., and Fueg, E., Demonstration of Low-Salinity EOR at Interwell Scale, Endicott Field, Alaska, SPE 129692, 2010).

Knowledge of the saturation of oil and water is very important for managing the operation of a depleted field. Saturation changes within the reservoir are indicative of the sweep of the oil reservoir by the displacement injection water, and the amount of oil released from the porous reservoir. However, tracking changes in saturation in an oil reservoir by itself does not provide information on the incremental oil production due to low salinity waterflooding.

A method for determining the amount of oil produced by a low salinity waterflood versus the amount of oil that would have been produced by a high salinity waterflood, such as a seawater flood, is important to better manage the operation of a low salinity waterflood. It is especially important when low salinity waterflooding is carried out by a secondary recovery method, either when a new oil well is brought into production from the reservoir, or after primary production under the influence of natural reservoir pressure, since there is no background high salinity waterflooding, from which the recovery can be determined. additional oil.

The essence of the invention

In accordance with a first aspect of the present invention, there is provided a method for detecting the production of additional oil (oil recovery) from an oil-bearing formation through which at least one injection well and at least one production well passes, during which a background oil sample is taken and the background oil sample is analyzed for determination of background compositional distinctive features for oxygenated organic compounds in oil;

low salinity waterflooding begins by injecting low salinity water into the oil reservoir through an injection well;

extract oil from the production well;

taking oil samples after waterflooding from a production well for a long time;

- 1 036572 analyze oil samples after waterflooding to determine compositional distinctive features for oxygen-containing organic compounds in oil after waterflooding;

identifying the difference between one or more groups of compositional signatures for oxygenated organic compounds in oil after flooding and background compositional signatures for oxygenated organic compounds in oil, characteristic of additional oil released through low salinity waterflooding.

By distinguishing between one or more groups of post-flood compositional signatures for oxygenated organic compounds in oil and background compositional signatures for oxygenated organic compounds in oil, release of additional oil during low salinity waterflooding can be detected. The method provides valuable information related to the appearance of additional oil in a production well.

In accordance with a second aspect of the present invention, there is provided a method for detecting the production of additional oil from an oil-bearing formation consisting of several layers of porous reservoir rock, and through this formation there is at least one injection well, at least one production well and at least one observation well located between the injection well and the production well, in the implementation of which the logging equipment is introduced into the observation well;

water with low salinity is injected into the reservoir through the injection well and oil is extracted from the production well;

using the logging equipment for a long time to determine the time interval t1 between the start of injection into the formation of water with low salinity through the injection well (s) and the detection of the front of the appearance of water with low salinity in the observation well;

determining the distance L1 between the injection well (s) and the observation well and calculating the speed v with which the front of low salinity water propagates in the oil reservoir, where v = L ₁ / t ₁ ;

determining the distance L2 between the observation well and the production well (s) and using the front propagation velocity v to predict the time t ₂ when the low salinity water will break into the production well, t ₂ = t1 + L ₂ / v;

a background oil sample is taken from the oil reservoir and analyzed to determine the distinguishing features of the background composition for oxygen-containing organic compounds in oil;

oil samples are taken after waterflooding, produced from the production well (s) for a long time, and oil samples are analyzed to determine the distinguishing characteristics of the composition after waterflooding for oxygen-containing organic compounds in the oil to detect differences between one or more groups of distinguishing characteristics of the composition after waterflooding for oxygenated organic compounds in oil and distinguishing features of the background composition for oxygenated organic compounds in oil, which are characteristic of additional oil released by waterflooding with low salinity;

increase the frequency of sampling of the produced oil after waterflooding as it approaches the predicted time t ₂ when the injected water with low salinity breaks into the production well, and exploits the revealed difference between the distinguishing features of the composition for oxygenated organic compounds in oil after waterflooding and background distinctive features composition to determine the point in time when additional oil breaks into the production well.

By using an observation well to determine the point in time when low salinity water breaks into the production well, post-flood oil samples can be more efficiently taken around the predicted point in time. Thus, for example, unnecessary sampling will not be required.

Other features and advantages of the invention will become apparent from the following description of preferred embodiments of the invention, given by way of example, with reference to the accompanying drawings.

Brief Description of Drawings

FIG. 1 is a schematic diagram illustrating a system for displacing crude oil from a formation that can be reconstructed in accordance with embodiments of the invention;

in fig. 2 is a flowchart illustrating a method for detecting additional oil production from a reservoir;

in fig. 3 depicts a system for performing any of the methods of the present invention;

in fig. 4 is a block diagram illustrating a method for back-matching a low salinity formation simulation to formation measurement data;

- 2 036572 in Fig. 5 is a schematic drawing showing the location of an observation well between an injection well and a production well;

in fig. 6 is a block diagram illustrating a method for detecting additional oil production from an oil reservoir consisting of several layers of porous reservoir rock when at least one injection well, at least one production well and at least one observation well located between the injection well and the production well;

in fig. 7 presents the data of mass spectrometry of ion-cyclotron resonance with Fourier transform (FT-ICR-MS - from English Fourier Transfrom Ion Cyclotron Resonance Mass Spectrometry), demonstrating the dependence of the carbon number (molecule size) on the equivalent mass of a prepolymer containing 1 mol of vinyl bonds ( DBE - from the English Double Bond Equivalent) for homologous compounds of class CxH _y O ₂ for oil samples taken during a coreflood experiment (Example 3);

in fig. 8 presents data from high-resolution time-of-flight mass spectrometry (HR-TOF-MS), showing the dependence of the carbon number (molecule size) on the equivalent mass of a prepolymer containing 1 mol of vinyl bonds ( DBE) for homologous compounds of the class CxH _y O ₂ for oil samples taken during a coreflood experiment (Example 3); and in FIG. 9 presents HR-TOF-MS data showing the carbon number (molecule size) for homologous compounds of the CH _y O ₂ class with DBE values of 1.

Definitions

The following terms are used in the description below.

The supplemental oil is the supplemental oil recovered by injecting low salinity water on top of conventional high salinity water injected.

The background oil sample is a moving oil sample. The term mobile oil is well known in the art and refers to oil that can naturally move in the formation.

The oil sample after waterflooding is the oil sample taken after the start of the injection of water with low salinity into the injection well.

Formulation hallmarks for oxygenated organic compounds are the relative amount of one or more oxygenated organic compounds in the oil.

High-resolution mass spectrometry (HRMS) is a mass spectrometric analysis that provides spectra of the mass / charge ratio (m / z) with an accuracy of four digits.

The expression oil-bearing zone displaced by a displacing agent is well known to those skilled in the art and means a part of an oil-bearing formation where oil saturation is increased through the use of enhanced oil recovery technology for stationary oil.

The term low salinity water means water with an RTOS in the range from 200 to 12000 parts per million by volume (ppmv), preferably from 500 to 10000 ppmv, more preferably from 500 to 5000 ppmv, in particular from 500 to 2000 ppmv, having a content polyvalent cations less than the content of polyvalent cations in the relict water of the oil reservoir. The ppmv unit corresponds to the unit mg / l. It should be understood by a person skilled in the art that water with low salinity has a low ionic strength, for example, has an ionic strength of less than 0.15 mol / l, in particular less than 0.1 mol / l.

The term high salinity water means water with a salinity of at least 15,000 ppmv, preferably at least 20,000 ppmv, more preferably at least 30,000 ppmv, in particular salinity in the range from 30,000 to 350,000 ppmv. Water with high salinity can be seawater, estuary water, saline water, saline produced formation water, saline water of an aquifer, or mixtures thereof.

Secondary waterflooding refers to waterflooding that occurs either after oil is recovered from an oil reservoir under the natural pressure of the reservoir (so-called primary production), or at the beginning of oil production from the oil reservoir (with the omission of primary production).

Low salinity tertiary waterflooding is a low salinity waterflooding performed after a secondary high salinity waterflooding.

Detailed description of the implementation of the invention

FIG. 1 is a schematic diagram simplifying the system 100 for producing crude oil from an offshore oil field. As shown in the drawing, several production wells 1a-1d are used to produce oil from at least one geological horizon forming the oil reservoir 3. Each production well 1a, 1b, 1c, 1d has a tubing string 5a, 5b, 5c, 5d installed therein and is equipped with wellheads 9a, 9b, 9c, 9d, respectively. Accordingly, the tubing string of each production well 3 036572 serves to transport fluids, including crude oil, produced from the oil reservoir 3 to the wellhead. From wellheads 9a, 9b, 9c, 9d, the recovered fluids are transferred to a flowline 7a, 7b, 7c, 7d to a manifold 8 connecting the flowlines to the main production pipeline 11, which transfers the produced fluids to production equipment 13 located on the platform or floating installation for production, storage and offloading of oil (FPSO - from the English.Floating Production, Storage and Offloading), on the riser 17. In addition, to the main production pipeline 11 can be connected to an additional oil reservoir (one or more oil reservoirs, each of which has several production wells), for example, summarized in part 15. The crude oil production system 100 also includes at least one, preferably several injection wells 10 for injecting a water-based displacement fluid (injection water) into the geological horizon of the oil reservoir 3 (similarly , the additional (s) oil (s) formation (s) of part 15 each has at least one at an injection well, preferably several injection wells). The first main injection line 12 for high salinity water under pressure (for example, seawater or associated formation water separated from crude oil in production equipment 13) and the second main injection line 14 for low salinity water under pressure (obtained using desalination equipment located on the platform or FPSO) pass from the production equipment 13 to the subsea reservoir 16 for delivery to the oil reservoir 3. Some crude oil production systems have one main injection line that can be used for water with low and high salinity. Special injection line (s) 18 extends from subsea reservoir 16 to injection well (s) for oil formation 3. Moreover, the first and second main injection lines 12, 14 may lead to one or more additional reservoir (s) 20 for each of additional oil reservoir (s) of part 15. A controller (not shown) is used to control the operation of the valves of the manifold (s) 16, 20 so that the dedicated injection lines 18 can be switched between receiving low salinity high pressure water and high salinity water high pressure.

Although FIG. 1 shows wellheads 9a, 9b, 9c, 9d of production wells 1a, 1b, 1c, 1d, located on the seabed in shallow water, tubing strings can be connected to the wellhead located on the platform. Likewise, the injection strings of injection wells 10 may be connected to wellheads located on the platform. Accordingly, in such a case, no subsea flowlines 7a-7d or manifold 8 are required.

Each oil reservoir 3 includes at least one geological horizon with porosity and permeability, such as sandstone.

The system for displacing the crude oil of the production system 100 typically includes equipment for injecting a water-based displacement fluid (injection water), such as seawater or low salinity water, into one or more oil-bearing reservoirs 3. For example, the displacement system typically contains one or more water-based drive fluid injection wells 10 (as shown in FIG. 1), one or more water-based drive fluid injection lines; and a controller adapted to control the injection of the water-based drive fluid. The displacement system may also include equipment associated with treating a water-based displacement fluid being prepared for injection, such as desalination equipment.

Although the crude oil recovery system 100 shown in FIG. 1 is intended for an offshore oilfield, the present invention can also be used in an onshore crude oil recovery system.

The water-based displacement fluid is injected by the injection equipment of the crude oil displacement system into its injection well (s) 10. The water-based displacement fluid then passes through the geological horizon containing crude oil and formation water, as a result of which the crude oil is displaced from the pore space geological horizon. The oil can then be transferred through the formation to a production well 1a-1d, which is located at a distance from the injection well 10 and from which the oil is being recovered.

By identifying changes in oil chemistry signatures from production wells 1a-1d, additional oil release during low salinity waterflooding can be detected. This is possible because certain changes in the signature of the oil composition indicate additional oil. Thus, the present invention provides a means for obtaining valuable information related to the occurrence of additional oil in the production well 1a-1d. In particular, it is also possible to detect the breakthrough of low salinity water into production well 1a-1d during low salinity waterflooding.

Accordingly, in FIG. 2 is a flow diagram of a method 200 for detecting additional oil production from an oil-bearing formation 3 through which at least one injection well 10 and at least one production well 1a-1d are passing. At 202, the method includes

- 4 036572 background oil sampling and analysis of the background oil sample to determine the background distinctive features of the composition of oxygen-containing organic compounds in oil. The background characteristics of the composition can be established in various suitable ways, described in more detail below.

Multiple mobile oil background samples may be taken to determine stable background signatures of the composition of oxygenated organic compounds in the mobile oil. For example, an average, such as an arithmetic mean, of the background features can be calculated. It is believed that one or more of these background moving oil samples may be discarded if the oil sample is contaminated, for example, with drilling fluids or completion fluids used in drilling and completing production wells 1a-1d. Therefore, it may be preferable to take baseline oil samples several days or weeks after the start of oil production from the production well 1a-1d.

In the case of tertiary waterflooding with low salinity, a background sample of mobile oil may be obtained from reservoir 3 during primary production, during a conventional waterflood with high salinity water, such as seawater, or it may represent an oil sample after waterflooding from an area of low salinity injection water should penetrate.

In the case of secondary waterflooding with low salinity, a background sample of mobile oil can be recovered from oil reservoir 3 during primary production (if this stage is not excluded), or it can be an oil sample taken after waterflooding from an area of the formation into which the injected water with low mineralization. For example, an oil sample after waterflooding can be taken either from an area of the reservoir, which is still to be penetrated by injected water with low salinity, or, in the case of a pair of injection and production wells, it can be extracted from a production well during the initial phase of secondary waterflooding with low salinity. mineralization, i.e. before the low salinity waterflooding front has time to travel a significant distance through the oil reservoir from the injection well to the production well.

At step 204, low salinity waterflooding begins when low salinity water is injected into the oil reservoir 3 from injection well 10. At step 206, fluids including crude oil are recovered from injection wells 1a-1d. In step 208, one or more post-flood fluid samples are taken from fluids produced from production wells 1a-1d over an extended period of time. Methods for sampling produced fluids are well known in the art. For example, post-flood samples can be taken downhole in production wells 1a-1d, wellheads 9a-9d, flow lines 7a-7d, or reservoir 8. Produced fluid samples after flooding can be at elevated pressure or at normal pressure. ...

Typically, samples of produced fluids after waterflooding are separated in a laboratory located either outside the production facility or in it. In the case of pressure samples, the post-flood samples are separated into a gas phase, an oil phase and an aqueous phase, and post-flood oil samples are taken from the separated oil phase. In the case of a sample under normal pressure, the samples after waterflooding are separated into an oil phase and an aqueous phase, and oil samples after waterflooding are taken from the separated oil phase.

Samples of produced fluids from production wells 1a-1d after waterflooding (and hence oil samples after waterflooding) can be taken either continuously or intermittently. If samples of produced fluids after waterflooding (and thus oil samples after waterflooding) are taken intermittently, the sampling frequency may increase over time towards the time when additional oil is expected to break into the production well. As shown above, the first oil samples after waterflooding, taken before the additional oil breakthrough into the production well, can be used as background oil samples. At step 210, a post-flood oil sample (b) is analyzed to determine post-flood compositional signatures for oxygenated organic compounds in the oil.

In step 212, a distinction is made between one or more compositional signatures for the oxygenated organic compounds in the post-flood oil and the background compositional signature for the oxygenated organic compounds in the oil, which is characteristic of the additional oil released by the low salinity waterflood. Compositional differences for oxygenated organic compounds were found to be observed when additional oil from low salinity waterflooding was discharged into production well 1a-1d. Thus, changes in the oxygenated organic compounds in the oil serve as an unmasking or distinguishing feature of the release of additional oil during low salinity waterflooding. Method steps 210 and 212 will be discussed in more detail below in relation to analytical high resolution mass spectrometry (HRMS) methods.

The distinction between compositional characteristics after waterflooding can be established by various suitable methods. For example, when background compositional signatures and post-flood signatures may be expressed as a single number, the difference may be expressed as an increase, decrease, or change. For example, the detected difference may be an increase, decrease, or change of at least 75%, at least 50%, at least 25%, or at least 10%.

The present invention provides better control of low salinity waterflooding and thus allows for the optimization of additional oil recovery from the reservoir. For example, identifying the difference between one or more of the compositional signatures for oxygenated organic compounds in oil after waterflooding and the background compositional signatures for oxygenated organic compounds in oil that is characteristic of additional oil released by low salinity waterflooding can be used in as a surveillance tool to detect movement of additional oil through the reservoir during low salinity waterflooding

to confirm that additional oil has been produced from the production well;

to determine the moment of stopping the injection of water with low salinity into the injection well and the moment of starting the injection of water with low salinity into another injection well;

to locate wells that seal the original well pattern, to optimize the movement of low salinity water through an oil reservoir, or to quantify the volume of additional oil produced by low salinity waterflooding.

For example, it may be determined that the amount of additional oil produced by low salinity waterflooding is relatively small, and it can be determined that it is more cost effective to start a high salinity waterflood instead.

Compositional signatures for oxygenated organic compounds in background oil samples and post-flood oil samples can be generated using any suitable analytical method, in particular high resolution mass spectrometry (HRMS). In one example, the high resolution mass spectrometer may be part of appropriately positioned measurement equipment 22, as shown in FIG. 1. This measurement equipment can be part of production equipment (for example, located on a platform or FPSO) or located in a remote laboratory. The data received by the measuring equipment 22 can be analyzed on site or remotely.

When using HRMS, the resolution can be expressed as (m / Am). where Δm is the width of the peak at a height that is a fraction of the maximum peak height. According to a generally accepted rule well known to those skilled in the art, Δm is defined as the full width of a peak at a height that is half its maximum height (FWHM). The high resolution mass spectrometer used in the present invention typically has a resolution greater than 50,000 FWHM, preferably greater than 100,000 FWHM, at an m / z ratio of, for example, 400. High resolution mass spectrometers suitable for use in the present invention include ion mass spectrometers. Fourier transform cyclotron resonance (FT-ICR), high-resolution time-of-flight mass spectrometers (HR-TOF), sector mass analyzers using a static electric sector or magnetic sector, or a combination of both, as a mass analyzer, or mass spectrometers with an ion trap (IT - from the English ion trap).

Usually, the intensity of the numerical m / z data is then normalized (where m is the mass and z is the charge) relative to the total intensity of the selected class of homologous organic compounds (preferably relative to the total intensity of specific DBE sequences within the selected class of homologous organic compounds) with the generation of a data table containing normalized relative intensity data for assigned organic ions. The class or range of homologous organic compounds used to normalize the intensity may depend on the type of oil sampled and the ionization method used for mass spectral analysis. Typically, the class or series of homologous organic compounds used to rate the intensity is a common and stable class or series of homologous organic compounds naturally found in oil that do not experience significant changes in intensity during low salinity waterflooding and, in particular, do not change. significant intensity in case of additional oil breakthrough. In particular, one or more internal standards at a known concentration (s) can be added to crude oil samples, allowing the samples to be analyzed to be compared at different times using the same instrument, or to samples analyzed by different instruments. An example of a suitable internal standard is a fluorinated organic compound such as fluorinated acid, since fluorinated organic compounds are not found in natural crude oils. The advantage of using a fluorinated organic compound is also the fact that fluorine has a different mass defect compared to hydrogen, as a result of which the peaks of ionized

- 6 036572 fluorinated organic compounds are in a different region of the m / z mass spectrum than the peaks of ionized organic compounds that make up the crude oil. It should be clear to the person skilled in the art that adding internal standard (s) to oil samples will improve the accuracy of normalizing the intensity of numerical m / z data. In this case, the intensity normalization can be performed relative to the intensity of the internal standard (s)

This creates tables of normalized numerical data for the background oil sample and for oil samples after waterflooding. One or more subgroups of these datasheets may be analyzed to identify differences in compositional signatures for oxygenated oil samples after waterflooding versus a background oil sample, characteristic of additional oil released during low salinity waterflooding. Preferably, one or more subgroups of data tables are used to build an array of dependencies, the comparison of which allows identification of any changes in the distinguishing features of the composition of oxygenated organic compounds.

Preferably, the ionization techniques used in HRMS studies ionize oxygenated organic compounds to produce charged molecules (ions) and minimize the fragmentation of these ions.

Oxygenated compounds found in crude oil are generally categorized into:

1) acidic compounds, for example linear aliphatic carboxylic acids, branched aliphatic carboxylic acids, monocyclic naphthenic acids, bicyclic naphthenic acids, polycyclic naphthenic acids, aromatic acids, bicyclic aromatic acids, polycyclic aromatic acids, phenols and cresols; and

2) non-acidic compounds such as ethers, aldehydes, ketones, benzofurans and dibenzofurans.

Any suitable ionization method can be used to ionize oxygenated organic compounds, including electrospray ionization (-), which is capable of ionizing oxygenated organic compounds such as phenols and carboxylic acids, and nitrogen compounds such as pyrroles and pyrrolidines; ionization by electrospray of positive ions (ESI (+) - electrospray ionization (+)), capable of ionizing nitrogen-containing organic compounds, such as amines and pyridines, and sulfur-containing organic compounds; photoionization of negative ions at atmospheric pressure (APPI (-) - atmospheric pressure photoionization (-)), capable of ionizing aromatic hydrocarbons, phenols, pyrroles, carboxylic acids and sulfur-containing hydrocarbons; and photoionization of positive ions at atmospheric pressure (APPI (+) - atmospheric pressure photoionization (+)), capable of ionizing aromatic hydrocarbons, non-acidic oxygen-containing organic compounds, phenols, cresols, pyrroles, pyridines and sulfur-containing hydrocarbons, such as thiophenes. Each of the other ionization methods used gives a different spectrum characterizing the oil sample. In an embodiment of the invention, the mass spectral analysis of oil samples preferably employs one ionization method, namely ESI (-).

When using ESI (-), the voltage at the input of the mass spectrometer is set so as to ionize the sample molecules when injected into the ionization source, but without their noticeable fragmentation. The voltages used in HRMS that achieve ionization but minimal fragmentation are well known to those skilled in the art.

With APPI, ionization is achieved by a different mechanism. Typically, the sample is exposed to ultraviolet radiation, which excites molecules in the oil sample with the loss of electrons by the molecules and the formation of radical cations. Ions can also be generated indirectly through the excitation of a dopant such as toluene, which can be added to the oil sample.

Preferably, the oil samples are diluted with an organic solvent or a mixture of organic solvents prior to ionization. Preferred solvents for ESI (-) ionization include mixtures of aromatic solvents (eg benzene, toluene or xylene, preferably toluene or xylene) with an alcohol (eg methanol, ethanol or 2-propanol, preferably methanol). Preferably, the aromatic solvent and alcohol are mixed in a ratio of 1: 1 to 3: 1, in particular about 1.5: 1. Optionally, a base is added to the solvent mixture to aid in the ionization of oxygenated organic solvents. Preferred bases include ammonia or ammonium hydroxide solutions. Preferably, the concentration of ammonia in the solvent mixture is from 0.1 to 2% by volume (based on the addition of 35% by volume ammonia solution to an alcohol such as methanol, ethanol or 2-propanol).

Diluted oil samples can be injected into the mass spectrometer using any suitable method of injection, including direct injection, or, in the case of liquid chromatography-mass spectroscopy (LC / MS), using flow injection analysis (FIA). analysis), by removing the liquid chromatography column and introducing the sample into a continuous stream of carrier fluid, preferably a carrier fluid. The carrier liquid for the LC / MS spectrometer can be an organic solvent, and suitable organic solvents are good

- 7 036572 known to those skilled in the art.

When HRMS is used as the analytical method, changes in compositional signature for oxygenated organic compounds indicative of the release of additional oil from low salinity waterflooding include one or more of the following:

1) increasing the total normalized signal intensity of the class of homologous compounds with the general formula CxHyOn, in which x is an integer in the range from 5 to 100, preferably from 8 to 75, more preferably from 8 to 60, in particular from 10 to 45; y - integer <2x + 2; and n is an integer in the range from 1 to 10, preferably from 1 to 5, more preferably from 1 to 3, in particular 2;

2). reducing the intensity of the weighted value of the equivalent weight of the prepolymer (DBE) for a class of homologous compounds with the general formula CxHyOn, in which x, y and n are defined above;

3) an increase in the total normalized signal intensity of the class of homologous compounds with the general formula CxH _y O _n (DBE = 1), in which x, y and n are defined above.

The reliability of using changes in oxygen-containing compounds, which serve as a unmasking or distinctive feature of the additional oil recovered during waterflooding with low salinity, increases with an increase in the specificity of the class of homologous compounds. For example, an increase in the ratio of the total signal intensities of a class of homologous compounds with the general formula C _x H _y O _n (DBE = 1), in which x, y and n are defined above, and n = 2, can serve as a characteristic indicator of additional oil released during waterflooding with low salinity.

It is known to those skilled in the art that the DBE parameter expresses the degree of unsaturation of an organic compound. The assignment of DBE values to each of the formulas based on m / z numerical values of the mass spectrum is a common method of analysis. A DBE of 1 corresponds to either one π bond (C = C bond or C = O bond) or one closed, fully saturated ring. It can be noted that saturated aliphatic monocarboxylic acids and saturated ketones have a DBE of 1; monocyclic naphthenic acids having a single carboxylate functionality and no ethylenically unsaturated sites have a DBE of 2; phenol and methylphenol (cresol) have DBE = 4; benzoic acid and phenylacetic acid have DBE = 5; and benzofuran has DBE + 6. Thus, the decrease in the intensity-weighted DBE value for the class of homologous compounds with the general formula C _x H _y O _n , in which x, y and n are defined above, is evidence of a high degree of saturation of oxygenated organic compounds in the additional oil resulting from waterflooding with low mineralization.

Shown in FIG. 3, system 300 can be used to determine the recovery of additional oil from the production well 1a-1d. System 300 includes a high resolution mass spectrometer (HRMS) component 304 that can analyze spectra of oil samples obtained using HRMS equipment. In one example, HRMS equipment may be part of a suitably positioned metering equipment 22 shown in FIG. 1 and 3.

In one design, MRR analysis component 304 is executed by a processing system 300 comprising a conventional operating system and a system bus coupled to a central processing unit (CPU) 318, hard disk drive 316, random access memory (RAM) 328, I / O interface 320, and network providing connectivity to user input / output devices and connections to other devices on the network 322. RAM 328 contains operating system software 302 that controls, in a known manner, the low-level operation of data processing system 300. RAM 328 contains an HRMS analysis component 304, an operating mode component 306, and an operating oil reservoir model 308. The configuration of each of these components can be changed based on the results of measurements and / or specified data stored in the database (DB) 326 or other memory component, functionally associated with or connected to the system 300 processing.

The measurement data obtained by the receiving means of the system 300 is based on the measured characteristics of the oil reservoir 3 and the water-based displacement fluid, as will be shown below. The measurement data may contain specific measured values directly obtained by appropriately placed measurement equipment 22, for example, measurement equipment containing HRMS equipment and, optionally, specific measured values directly obtained by a logging tool within a suitably located observation well, which can, for example, measure the water saturation of the formation. or the salinity of the water contained in the tank. Other measurement data may contain ratios of characteristic values or may contain values obtained from independent measurements of characteristics according to known methods. In this case, the raw characteristic measurements can, if necessary or preferably, be processed using suitable software by the CPU 318 of the system 300 to obtain measurement data suitable for input into the formation model 308, the HRMS component 304 or the operational component 306. Such processing may include simply converting units of measure or creating the desired ratio of measured values.

- 8 036572

The system 300 may be operatively coupled to a controller 324 of a system of displacement of crude oil from the formation, for example, through the network 322. The controller 324 of the system of displacement automatically adjusts itself to one or more modes of operation determined by the system 300; controller 324 is then adapted to use one or more modes of operation.

The method 200 shown in FIG. 2 may be implemented in whole or in part by system 300. Measurement data related to background oil samples or post-flood oil samples may be acquired by metering equipment 22 connected to network interface 320. For example, HRMS data may be acquired by system 300 and stored on hard disk 316. The HRMS analysis component 304 contains software executed by the CPU 318 to analyze data from HRMS equipment to distinguish the composition of an oil sample. Thus, the analysis component 304 HRMS analyzes or manages data associated with background oil sample (s) or post-flood oil sample (s). Data can be optionally displayed on a computer monitor or saved for later use.

Analysis HRMS component 304 may also be programmed to identify differences between one or more OOC signatures in oil after flooding and background OOC signatures in oil associated with additional oil released by low salinity waterflooding. Alternatively, such identification can be done manually.

In low salinity tertiary waterflooding, OOC signature changes typically occur in the displaced oil zone that breaks into production well 1a-1d. Accordingly, changes in the signature of the composition of oxygenated organic compounds in oil can be used as a monitoring tool during low salinity waterflooding to determine when the displaced oil zone reaches the production well 1a-1d. Typically, the oil zone reaching the production well corresponds to an increase in the oil / water ratio in the fluids produced from the well.

One of ordinary skill in the art will appreciate that when a low salinity waterflooding is performed in a tertiary recovery mode after a conventional high salinity waterflood, the mobile oil has already been largely displaced from the reservoir so that the low salinity water serves to release the porous formation from the surface. oil adhered to it and the movement of the formed mobile zone to the production well. In contrast, when low salinity waterflooding is performed in a secondary recovery mode, the function of low salinity water is to move mobile oil (i.e. oil that would have been recovered using conventional high salinity waterflooding) before low salinity water to production water. well and the release of adhered additional oil from the surface of the formation porous rock. Without going into the theory of the issue, thereby a movable zone of additional oil is formed between the waterflood front with low salinity and the trailing front of mobile oil, thereby prolonging the period of dewatered oil production before the injection water breakthrough into the production well (in comparison with the period of dewatered oil production during conventional waterflooding with high mineralization). Dispersive mixing can occur between the displaced oil zone and the mobile oil. Accordingly, the difference in the distinguishing features of the composition of oxygenated organic compounds upon breakthrough of additional oil in the production well may be less noticeable in the secondary recovery method than in the tertiary recovery method. Therefore, low salinity secondary flooding may require more frequent sampling and analysis of the produced oil than tertiary low salinity waterflooding.

One of ordinary skill in the art will also appreciate that the amount of additional oil that can potentially be produced from an oil reservoir during low salinity waterflooding can be determined by (1) taking a core from a porous reservoir sample and performing a coreflood experiment using background secondary flooding with high salinity, such as seawater flooding followed by tertiary flooding with low salinity, or (2) taking two related cores from a porous reservoir sample and performing secondary flooding with low salinity on the first core and secondary background waterflooding with high mineralization on the second core. Related pillars are rock samples taken from a part of the core with similar rock properties. These coreflood experiments can be conducted either in oil reservoir conditions or in simplified conditions. The simplified coreflood test uses free gas fluids (crude oil and water containing no gas), while the oilfield coreflood test uses free gas fluids (crude oil and water, combined with gas having the same or similar composition as the gas separated from the produced fluids in the production equipment). In both cases, the sample is crude

9 036572 oil is preferably taken from the same oil reservoir as the porous reservoir samples. Variations in the signature composition of oxygenated organic compounds in oil produced during a low salinity coreflood experiment relative to oil produced in a background high salinity coreflood experiment can then be compared to additional oil production during a coreflood test with low mineralization. In particular, for this comparison, the normalized intensity of the relative signal of one or more of the classes of homologous oxygen-containing organic compounds defined above, characteristic of the additional oil released due to core flooding with low salinity, can be used. A coreflood experiment can thus be used to identify compositional signatures for the most abundant and / or most abundant OOCs and / or the most prominent additional oil that could potentially be recovered from an oil reservoir during low salinity waterflooding.

In one aspect of the present invention, a compositional change for oxygenated organic compounds in oil versus a baseline oil sample can be used to back-match a low salinity waterflood model from measurement data obtained during low salinity waterflooding. Reverse adaptation of the reservoir simulator from measurement data is well known in the art. Backward adaptation involves adjusting the reservoir simulation until it accurately reproduces the reservoir's past behavior. The model thus adapted can be used to model future reservoir behavior with a high degree of confidence.

There are commercial oil reservoir simulators that simulate low and high salinity waterflooding. One such industrial simulator is Eclipse from Schlumberger. In addition, GRJerauld et al., Modeling Low-Salinity Waterflooding, SPE 102239 describes how to adapt an oil reservoir simulator to simulate low salinity waterflooding. Existing reservoir models, such as Eclipse, can simulate both low and high salinity waterflooding. For example, a simulated highly saline waterflood can predict that the total oil produced will be Y _high . mineral. By keeping all other conditions unchanged and simulating low salinity waterflooding, the model can predict that the total oil produced is Unizk. mineral. The amount of additional oil produced through the use of low salinity waterflooding is thus:

Udop. ^- Low. mineral. ^_ High. mineral. > GDS Lower Mineral> High mineral.

Although these conventional oil reservoir simulators simulate low and high salinity waterflooding to determine, inter alia, the amount of oil that would be produced by such waterflooding, the predicted quantities may not be accurate. For example, the simulated quantity (s) may not be the same as the actual waterflooding for a particular oil reservoir. One source of modeling error can be uncertainty in the input data of the models. Uncertainty in the model inputs can affect the simulation results. Reverse model matching involves modifying the input to the model and comparing the simulation results with what is observed / measured during the actual waterflooding. The step of changing the input data can be performed iteratively until a good match is achieved between the simulation output and the measurement results. For example, the difference between the simulation results and the measurement results can be reduced until the difference becomes less than an acceptable threshold, for example, a deviation of less than 10%, more preferably less than 5%, even more preferably less than 1% between the simulation output and the measurement results. In other examples, absolute thresholds can also be used, for example, the absolute value of the tolerance is determined.

Once a back-adapted model is obtained, the amount of additional oil that will be produced from low salinity waterfloods can be calculated. To do this, a comparison of the simulated volume of oil produced by high salinity waterflooding is performed with the simulated volume of oil produced by low salinity waterflooding. The predicted amount of additional oil is likely to be closer to the real as the models have been back-fitted. In this case, the decision to conduct waterflooding with low salinity can be made based on the predicted volume of additional oil. For example, it may be more cost effective to perform high salinity waterflooding than to desalinate seawater if the predicted amount of additional oil is small.

One possible real / measured outcome that can be used in reverse adaptive modeling is the time it takes for additional oil to break into production wells 1a-1d. Alternatively or additionally, the measured volume of oil produced as a function of time can be used for backward adaptation of the model. This one measured

- 10 036572 The time at which additional oil breaks into the production well can be determined by method 200 of FIG. 2. As explained above, method 200 can detect the presence of additional oil in the produced oil. This can then be used to determine when additional oil will be found in production well 1a-1d after the start of low salinity waterflooding. Once the point in time has been measured when additional oil breaks into the production well of the oil reservoir, this value can be used to back-match the reservoir model.

As mentioned above, a reservoir simulator can be used to estimate the amount of additional oil that could potentially be produced during a reservoir-wide low salinity waterflood. An oil reservoir simulator is well known in the art and is used to simulate or simulate the injection of fluids into one or more layers of the reservoir through an injection well (s), the movement of fluids through the layer (s) of the reservoir, and the production of fluids from the layer (s) of the reservoir through the production well. (s). Typically, a static geological model of the reservoir is entered into the reservoir simulator. This static geological model is obtained by inputting seismic imaging data, petrophysical data associated with the layer (s) of the reservoir porous rocks (e.g., the porosity and absolute permeability of the layer (s) of the reservoir rocks), and the geological description of the layer (s) of the reservoir porous rocks (for example , mineralogical characteristics of the reservoir layer (s)) and fluid saturation data (for example, the original water saturation and the initial oil saturation of the reservoir), into a geological model, generating a 3-dimensional (3-D) oil reservoir model showing the layer (s) of reservoir porous rocks , oil traps, any imperfections or any areas of low permeability.

After the introduction of the static geological model into the reservoir simulator, the locations of the injection well (s) and the production well (w) are selected and entered into the reservoir simulator. Additional fluid data are also entered into the reservoir simulator, such as the characteristics of the relict water (for example, the RTOS in the relict water and the content of one or more individual dissolved ions), the characteristics of the oil (for example, the chemical composition, density and viscosity of oil), characteristics of the injected water low salinity (for example, RTOS in low salinity water and the content of one or more individual dissolved ions) and characteristics of the background injection water with high salinity (for example, RTOS in water with high salinity and the content of one or more individual dissolved ions). The reservoir simulator also introduces the relative permeabilities of the porous reservoir to oil and water, measured from the salinity of the low salinity injected water and the background high salinity injection water. If rock properties (porosity, absolute permeability, or mineralogical characteristics) change across the formation (for example, rock characteristics change between layers of porous reservoir rock or across the formation), the measured relative permeabilities for oil and water for other rock types are entered into the oil reservoir simulator. ... As is well known to those skilled in the art, the relative permeabilities of a porous formation to oil and water can be determined from coreflood experiments performed on formation rock samples in an oil formation. Typically, the relative permeabilities of a porous reservoir for oil and water are measured as a function of increasing water saturation (decreasing oil saturation) and plotting relative permeability curves. As explained in G.R. Jerauld et al., Modeling Low-Salinity Waterflooding, SPE 102239, relative permeability and capillary pressure are a function of salinity. Relative permeability curves for high and low salinity are entered into the reservoir model and can be interpolated for intermediate salinity values.

Data relating to the characteristics of low salinity water and to the relative permeabilities of the porous formation for oil and water, measured at the salinity level of the low salinity water, is hereinafter referred to as the low salinity input data. The data relating to the characteristics of the background water with high salinity and to the relative permeabilities of the porous formation for oil and water, measured at the level of salinity of the background water with high salinity, hereinafter referred to as the input data of high salinity. The rest of the data entered into the reservoir simulator will hereinafter be referred to as general input data. For example, common inputs may include the location of an injection well (s) and a production well (s), and fluid data containing the connate water and oil characteristics associated with the porous layer (s) of the reservoir.

The reservoir simulator then uses the general and low salinity inputs to simulate as a function of time, the injection of low salinity water into the reservoir through the injection well (s), the movement of fluids through one or more layers of the reservoir, in particular the oil-bearing layer (s) , and recovering fluids from the formation through the production well (s), taking into account obstacles to flow in the geological model, for example, defects or loss of permeability of the formation porous rock. The resulting reservoir simulation thus produces a variety of low salinity outputs including:

- 11 036572 (a) sweep factor by volume for one or more layers of the oil reservoir;

(b) the point in time when water with low salinity breaks into the production well (s);

(c) pressure in the injection well (s) and production well (s), in particular the pressure in the injection well (s) and production well (s) at the depth (s) of the oil-bearing layer (s) of the formation; and (d) the volumes of oil and water produced from the production well (s) during waterflooding of the low salinity formation as a function of time (thereby obtaining a production profile of low salinity oil).

In some examples, the time it takes for additional oil to break into the production well (s) can also be modeled or inferred from the low salinity output.

It should be understood by one of ordinary skill in the art that one or more of (a) through (b) low salinity outputs, preferably all of (a) through (b) low salinity inputs, can be used as additional inputs to a reservoir simulator when calculating the volume (s) of oil and water that could be produced from the production well (s) during a low salinity waterflood as a function of time. The sweep ratio by volume indicates the portion of the reservoir that was or was not swept by the injected water.

The reservoir simulation can then be repeated using generic and high salinity inputs to produce high salinity outputs including:

(a) a sweep ratio by volume for one or more layers of the oil reservoir;

(b) the point in time when water with high salinity breaks into the production well (s);

(c) pressure in the injection well (s) and production well (s), in particular the pressure in the injection well (s) and production well (s) at the depth (s) of the oil-bearing layer (s) of the formation; and (d) the volumes of oil and water that would have been produced from the production well (s) during the high salinity waterflood as a function of time (thus obtaining a high salinity oil production profile).

It should be understood by one of ordinary skill in the art that one or more of the outputs (a) - (b) high salinity, preferably all of the inputs (a) through (b) high salinity, can be used as additional inputs to a reservoir simulator when calculating the volumes of oil and water that could be produced from a production well (s) during a waterflood with high salinity, as a function of time.

One of ordinary skill in the art will appreciate that at any given time, the difference in the volume of oil produced from the production well (s) between the simulated high salinity waterflood and the simulated low salinity waterflood is an estimate of the amount of additional oil that could potentially be produced during oil flooding. formation with low salinity.

Next, the backward adaptation of the model is performed by entering the formation measurement data into the formation model. This formation measurement data includes the point in time at which additional oil breakthrough was detected in the production well (s) (as determined by the detection of a change in compositional signature after waterflooding for oxygenates in oil versus background oil compositional signatures). Preferably, the oil reservoir measurement data also includes one of:

a) the volume of low salinity water injected into the injection well (s) as a function of time, for example the volume of low salinity water injected into each injection well per day;

b) the volume of oil produced from the production well (s) as a function of time, for example, the volume of oil produced from each production well per day;

c) the volume of water received from the production well (s) as a function of time, for example, the volume of water produced from each production well per day;

d) water cut of well production as a function of time (here, the water cut of well production means the ratio of the volume of water to the volume of oil produced from the formation), in particular, the water cut of well production for each production well as a function of time;

e) well pressures in the injection well (s) and production well (s) at the depth (s) of the oil-bearing layer (s) of the formation as a function of time;

f) mineralization of produced water as a function of time;

g) the concentration of selected ions in the produced water as a function of time, for example, the concentration of divalent cations, for example, magnesium or calcium cations as a function of time;

- 12 036572

h) the point in time when the breakthrough of water with low salinity into the production well (s) was detected;

i) in the case when the observation well penetrates into the oil reservoir (as will be shown below), the water saturation of the oil-bearing layer (s) of the formation porous rock surrounding the observation well, as a function of time and / or the salinity of water contained in the pore space of the oil-bearing layer (e ) porous reservoir rock surrounding the observation well as a function of time;

j) if available, four-dimensional (4D) seismic image data, i.e. seismic image data acquired at one or more points during the post-production of oil from the oil reservoir.

It then back-adapts the reservoir simulation output (including predicted oil production to simulate low salinity waterflooding) to the reservoir measurement data by adjusting input uncertainties (e.g., static geological model uncertainties, petrophysical uncertainties, or relative permeability data uncertainties). ). These adjustments continue until a match is achieved between the output of the oil reservoir simulator and the measurement of the reservoir. One of ordinary skill in the art will appreciate that as the low salinity waterflood continues, the backward matching step of the model can be repeated one or more times so that the simulation output of the oil reservoir matches the measurement of that reservoir exactly. Reverse adaptation of the low salinity waterflood model can be accomplished by adjusting the uncertainties of the low salinity inputs only, only the general inputs, or both. When the uncertainty in the generic inputs is corrected, the inversely adapted generic inputs can also be used in high salinity oil reservoir modeling.

The matched (inversely adapted) model (simulator) of the oil reservoir can then be used in a predictive mode to estimate the future production of additional oil from the reservoir due to low salinity waterflooding, or to justify the principles of improved waterflooding with low salinity of the oil reservoir, for example, modeling changes in quantities of low salinity water injected into one or more of the injection wells, or stopping the injection of low salinity water into one or more of the injection wells and starting the injection of low salinity water into one or more other injection wells.

In another aspect of the present invention, a change in composition signature for oxygenates in oil relative to background oil samples can be used to estimate the amount of additional oil produced from the oil reservoir. As shown above, back-matching of the oil reservoir model is performed after additional oil breakthrough into the production well (s) of the oil reservoir so that the predicted volumes of oil and water recoverable from low salinity waterflooding correspond to the actual volumes of oil and water produced from the reservoir. Reverse adaptation of the reservoir model is performed regularly as the low salinity waterflood progresses so that the predicted oil and water production from the reservoir simulator continues to closely match the actual oil and water produced from the reservoir. After back-matching the reservoir simulation output to the reservoir measurement, an estimate of the additional oil produced by the low salinity waterflood can be obtained by using the back-adapted reservoir simulator with the high salinity input. For example, a back-fitted simulator uses back-adapted common inputs or any other back-adapted inputs. The back-adapted reservoir simulator thus predicts the recoverable oil and water volumes that would be recovered from a high salinity background injection waterflood rather than a low salinity injection waterflood. The difference between the actual volume (s) of oil recovered from the production well (s) of the oil reservoir and the predicted volumes according to the inversely adapted reservoir model at high salinity gives an estimate of the volume of additional oil due to low salinity waterflooding. As shown above, back-matching of the low salinity reservoir model is performed regularly during low salinity waterflooding. Accordingly, each back-adapted simulation can be conducted using high salinity inputs, thereby generating estimates for additional oil production as low salinity waterflooding continues.

One of ordinary skill in the art will appreciate that when back-adapted simulations are performed using high salinity inputs, estimates can also be made for an extended dry oil recovery period provided by low salinity secondary flooding, or an extended low salinity water cut period.

- 13 036572 as a result of tertiary waterflooding with low salinity. Thus, the measured time for low salinity water to break into the production well (s) during low salinity secondary waterflooding, or the measured water cut for production well (s) fluids during tertiary low salinity waterflooding, can be matched with simulated breakthrough time (s) or simulated water cut when back-adapted reservoir simulations are performed using high salinity input data.

The system 300 shown in FIG. 3 can be used to back-match reservoir simulations to measured data. System 300 includes a reservoir model 308 that can simulate waterflooding. The reservoir model 308 includes a low salinity module 310 and a high salinity module 312. When the reservoir model 308 uses a low salinity module 310, it can be used to simulate low salinity waterflooding. When the reservoir model 308 uses high salinity module 312, it can be used to simulate high salinity waterflooding. The CPU 318 can use the reservoir model 308 to simulate multiple waterfloods simultaneously or separately. The formation measurement data used to back-adapt the simulation of the formation output can be obtained by model 308 from the HRMS analysis component 304. For example, this formation measurement data may include the point in time at which additional oil breakthrough into the production well (s) was detected (determined by the detection of a change in the O2 composition signature of the oil after flooding versus background oil composition signature). The additional reservoir measurement data listed above can be obtained by the reservoir model 308 from one or more databases 326, hard disk 316, or measurement equipment 22. The reservoir model 308 can then be back-adapted to more accurately predict the amount of additional oil produced by the waterflood. with low mineralization.

Based on the simulated reservoir simulation backward matching output, mode component 306 can, for example, determine when to stop the injection of low salinity water into an injection well and when to start injection of low salinity water into another injection well. The operating mode component 306 receives the results of the analysis performed by the reservoir model and can select multiple operating modes of the displacement system accordingly. The controller 324 of the system of displacement of crude oil is connected to the system 300. The controller 324 applies one or more operating modes determined by the component 306 of the operating mode. In another example, mode component 306 may determine which injection well 10 to inject low salinity water based on output from the oil reservoir model 308. For example, a reservoir model can predict that injection into one injection well will produce more additional oil than if water were injected into another injection well.

FIG. 4 is a flow chart illustrating a method 400 for backward matching a low salinity formation simulation to formation measurements. In one example, method 400 is performed using the formation model 308 shown in FIG. 3. Method 400 comprises, at 402, obtaining formation measurement data. For example, a production time can be determined when additional oil will break into the production well (s) during low salinity waterflooding using the method 200 described above with reference to FIG. 2. Additional reservoir measurement data that may be obtained include the measured volume (s) of oil recovered from the production well (s) during low salinity waterflooding, as a function of time.

In step 404, the method is loaded into the low salinity oil reservoir model with generic and low salinity inputs to simulate low salinity waterflooding, with the generic and low salinity inputs having associated uncertainties. At step 406, low salinity formation simulations are performed with generic and low salinity inputs to produce low salinity outputs, the low salinity outputs comprising one or more of:

the computed volumetric sweep factor for the layer (s) of the reservoir porous rock as a function of time;

the calculated moment (s) of time when the low salinity water will break into the production well (s);

calculated pressures in the injection well (s) and production well (s) at the depth of the oil-bearing layer (s) of the formation;

calculated volume (s) of oil recovered from production well (s) in low salinity conditions as a function of time.

At 408, the method generates an inversely adapted low salinity oilflood simulator by backward data adaptation

- 14 036572 low salinity to formation measurement data by adjusting uncertainties in the low salinity input. In some examples, generating an inversely adapted reservoir simulator includes adjusting uncertainties in the common inputs to obtain inversely adapted common inputs.

The method may optionally also include injecting a static three-dimensional (3-D) geologic model of the oil reservoir into the reservoir simulator showing the porous layer (s) and any obstruction (s) to flow and including petrophysical data, rock property data, and fluid saturation data for layer (s) of reservoir porous rock. In some examples, this input can also be tuned during back adaptation.

Optionally, the amount of additional oil recovered from the formation can be estimated as a function of time using the inverse adaptation of reservoir simulations conducted in accordance with method 400. The method for estimating the volume of additional oil as a function of time includes inputting high salinity input data into the back-adapted reservoir simulator to simulate waterflooding with high salinity;

running a back-adapted reservoir simulator using back-adapted generic high salinity inputs and outputs including the calculated volume (s) of oil recovered from the production well (s) in high salinity conditions as a function of time; and estimating the volume of additional oil by subtracting the calculated volume (s) of oil recovered from the production well (s), as a function of time in high salinity conditions, from the measured volume (s) of oil recovered from the production well (s) during the low waterflooding. mineralization of the reservoir, as a function of time. It should be clear to one of ordinary skill in the art that any or all of the inversely adapted input data can be used in the back adapted simulator.

As mentioned above, an observation borehole can be drilled through the oil reservoir, into which a logging tool can be lowered. For example, a logging probe may be placed in an observation well that can be used to measure the water saturations of the oil-bearing layer (s) of the porous formation or the salinity (total dissolved solids) of the water in the pore space of the oil-bearing layer (s) of the porous formation. FIG. 5 shows such an observation well 23 passing through an oil reservoir 3. In this example, an observation well 23 passes through the formation 3 between the injection well 10 and the production well 1a. Observation borehole 23 also contains a logging tool 24 that can, for example, measure the water saturation or salinity of water in the formation 3.

Changes in water saturation (and hence oil saturation) of one or more of the oil-bearing layers of the reservoir porous rock can be correlated with the extraction of additional oil from the production well. For a specialist it should be clear that a change in the water saturation of the oil-bearing layer (s) of the formation porous rock indicates a change in oil saturation, and the oil saturation is [100 - water saturation%]. Thus, for tertiary waterflooding with low salinity, when the displaced oil zone spreads over the reservoir area penetrated by the observation well, there will be changes in the water saturation of the oil-bearing layer (s) of the reservoir porous rock. In particular, when the displaced oil zone reaches the observation well, there is an increase in oil saturation and a decrease in water saturation of the formation porous rock (in comparison with the background oil saturation and water saturation of the formation porous rock at the beginning of low salinity waterflooding). When the trailing edge of the oil zone passes the observation well, there will be a decrease in oil saturation and an increase in water saturation of the formation porous rock (compared to the background oil saturation and water saturation of the formation porous rock at the beginning of the tertiary flooding of low salinity). It should be clear to those skilled in the art that after the trailing edge of the displaced oil zone has passed the observation well, the porous formation will enter a state of residual oil saturation S _or .

With secondary flooding of low salinity, there will be a decrease in oil saturation and an increase in water saturation of the reservoir porous rock when the trailing edge of the displaced oil zone passes the observation well (in comparison with the background levels of oil saturation and water saturation of the reservoir porous rock at the beginning of the secondary flooding with low salinity). The skilled person should understand that after the trailing edge of the displaced oil zone has passed the observation well, the porous formation will enter the state of residual oil saturation Sor.

Variations in the salinity of water contained in the pore space of an oil-bearing layer (s) of a reservoir porous rock can be used to monitor the rate of advancement of a low salinity flooding front in one or more oil-bearing layer (s) of an oil formation. At the same time, there will be a decrease in the mineralization of water contained in the pore space of the oil-bearing

- 15 036572 layer (s) as the low salinity waterflooding front moves past the observation well. The data associated with the discovery of low salinity water in the production well can then be used to back-adapt the oil reservoir simulator to achieve greater certainty in predicting when low salinity water will break through into the production well (s). This data can also be used to determine when to increase the frequency of oil sampling after waterflooding for the analysis of oxygenated organic compounds in the recovered oil.

In an article by G.R. Jerauld et al., Modeling Low-Salinity Waterflooding, SPE 102239, show how changes in oil saturation, water saturation and salinity occur as a function of distance from the injection well during secondary and tertiary low salinity waterflooding. Jerauld et al. show saturation jumps as a function of distance from the injection well at a particular point in time. These jumps refer to areas where salinity and saturation change suddenly as oil and water are moved through the porous reservoir. One of ordinary skill in the art will understand that by temporarily monitoring salinity and saturation, a low salinity water front passing by the observation well can be detected. For example, by plotting salinity or saturation versus time, the jumps described by Jerauld et al.

In another example, differences in baseline salinity and saturation measurements and post-flood measurements of these parameters may be found. Differences between one or more postflood measurements may be found, characteristic of a low salinity waterflood front. For example, the difference could be an increase, decrease, or wobble. For example, the detected difference can be an increase, decrease, or fluctuation of at least 50%, at least 75%, or at least 90%. Typically, the background salinity of water in the pore space of a porous reservoir can range from 15,000 to 350,000 ppmv. The salinity of water in the pore space of the formation pore rock after waterflooding, after the low salinity water front has passed the observation well, can be in the range from 200 to 12000 ppmv, preferably from 500 to 10000 ppmv, more preferably from 500 to 5000 ppmv.

In another example, a low salinity water front can be detected in an observation well by detecting the presence of a marker preparation that has been injected into the low salinity water. This marker preparation can be used to predict when waterflooding will reach low salinity of the production well.

FIG. 6 shows a method 600 for detecting the extraction of additional oil from an oil-bearing formation 3 containing several layers of porous reservoir rock, and through the formation 3 there is at least one injection well 10, at least one production well 1a and at least one observation well 23 located between injection well 10 and production well 1a, in which the logging tool 24 is inserted into observation well 23 at step 610. In one example, the logging tool detects the presence of a marker preparation in the water. In another example, logging tools 24 are used to monitor changes in water saturation of one or more layers of porous formation 3, changes in water salinity within the pore space of layer (s) of porous formation 3, or changes in both water saturation and water salinity. Method 600 can be performed in whole or in part by system 300.

In one example, the method also specifically uses logging equipment 24 to generate background measurement data from the readings. For example, background readings can be obtained for the water saturation of one or more oil-bearing layers of the formation porous rock 3, background readings of the salinity of water in the pore space of one or more oil-bearing layers of the formation porous rock 3, or background readings for both water saturation and water salinity. ... If the presence of a marker preparation is being performed to register a low salinity waterflood front, a background measurement may not be necessary.

At step 620, the method begins waterflooding by injecting low salinity water into the oil reservoir 3 from the injection well 10 and extracting oil from the production well 1a. In one example, a marker formulation is optionally added to low salinity water. The salinity of low salinity water may already be known.

At step 630 of the method, the logging equipment is used for an extended period of time. For example, logging equipment can be read over a long period of time after waterflooding in terms of water saturation of the oil-bearing layer (s) of the formation porous rock, salinity of water in the pore space of the oil-bearing layer (s) of the formation porous rock, or for water saturation and salinity together. In one example, post-flood logging readings are taken to detect the presence of a marker preparation.

- 16 036572

At step 630, a time period t _{1 is} also determined between the start of the injection of low salinity water into the oil reservoir from the injection well (s) and the detection of a low salinity water front in the observation well. For example, this step may identify the difference between one or more logging readings after waterflooding and background readings for the water saturation of the oil-bearing layer (s) of the reservoir porous rock, the salinity of the water in the pore space of the oil-bearing layer (s) of the reservoir porous rock, or both water saturation and water salinity so that this difference can be used to identify a change in the water saturation of the oil-bearing layer (s) of the reservoir porous rock or a change in both water saturation and salinity of water near the observation well, indicating that the observation well has reached a low salinity flooding front. In another example, the presence of a marker preparation is detected, indicating that a low salinity waterflood front has reached the observation well.

Step 630 also determines the distance L1 between the wells, namely between the injection well (s) and the observation well, and calculates the velocity v with which the low salinity water front advances, v = L ₁ / t ₁ . At step 630, the distance L2 between the wells, namely the observation well and the production well (s), is also determined, and the front advancement velocity v is used to predict the time t _{2 of the} breakthrough of low salinity water into the production well, where t ₂ = t1 + L ₂ / v. Distances L1 and L2 are indicated in FIG. 5.

At 640, a background oil sample is taken from the oil reservoir and analyzed to generate background compositional signatures for oxygenated organic compounds in the oil.

At step 650, a post-flood oil sample is taken from the oil recovered from the production well (s) and analyzed to generate compositional signatures for oxygenated organic compounds in the postflood oil to identify the difference between one or more sets of compositional signatures for oxygenated organic compounds. in oil after waterflooding and a set of background compositional signatures for oxygenated organic compounds in the oil, indicating the recovery of additional oil from low salinity waterflooding.

Step 650 is repeated with increasing frequency or decreasing measurement intervals as it approaches the predicted time t ₂ when the low salinity water breaks into the production well.

At 660, the differences found between the OOCs in the post-flood oil and the background signatures are found to determine when additional oil will break into the production well.

Any data on the residual oil saturation obtained for the oil-bearing layer (s) of the reservoir porous rock by measuring the water saturation of its layers after the trailing edge of the oil transfer zone (tertiary recovery method) or the trailing edge of additional oil by the secondary recovery method) past the observation well can also be entered into an oil reservoir simulator, such as reservoir model 308, for use in backward matching reservoir simulations to oil and water recovered volumes. For example, the logging tool may form part of the measurement equipment 22 shown in FIG. 3.

Baseline oil and post-flood samples are as described above.

In the event that there is more than one injection well 10 and more than one production well 1a-1d, it is desirable for each pair of injection and production wells to have an observation well 23.

The logging tool 24 may include a resistivity logging probe, a nuclear magnetic logging probe, or any other logging tool capable of identifying changes in the water saturation of the oil-bearing layer (s) of the porous formation or changes in the salinity of water in the pore space of the oil-bearing layers of the porous formation. If the logging tool 24 includes a resistivity logging probe or a nuclear magnetic logging (NMR) probe, the observation well preferably has fiberglass casing to prevent formation fluids from entering the observation well.

Preferably, observation well 23 is substantially parallel to production well 1a-1d. Preferably, observation well 23 is located close to production well 1a-1d such that changes in the water saturation of the formation porous layers 3 in observation well 23 are in good agreement with changes in the water saturation of the layers of porous formation 3 in production wells 1a-1d. Preferably, the observation well is located within 30.5 m (100 ft), more preferably within 15.2 m (50 ft) of the production well 1a-1d, in particular within 7.6 m (25 ft) of the production well. wells 1a-1d. A suitable distance of observation well 23 from production well 1a-1d is 3.0 to 30.5 m (10-100 ft), preferably 4.6 to 15.2 m

- 17 036572 (15-50 feet), in particular from 4.6 to 7.6 m (15-25 feet).

After waterflooding, oil samples can be taken either continuously or periodically, as described above. Preferably, analysis of baseline oil and post-flood oil samples for compositional signatures for oxygenated organic compounds in the oil can be performed using HRMS as described above.

The skilled person knows that water is usually produced together with oil from the production well (n) 1a-1d. Accordingly, fluids produced from an oil reservoir are typically separated in production equipment into oil phase, water phase and gas phase, and samples of the separated oil are further analyzed for oxygenated organic compounds, as described above. Optionally, samples can also be taken from the extracted water over a long period of time and analyzed for an increase in the concentration of one or more ions, for example, Fe ²⁺ , Ca ²⁺ , Mg ²⁺ and Sr2 ⁺ ions, in particular Ca ²⁺ and Mg2 ⁺ ions associated with the breakthrough of water with low salinity in production wells 1a-1d. The recovered water samples can also be analyzed for the reduction in total dissolved solids (salinity) associated with the breakthrough of low salinity water into production well (s) 1a-1d. One of ordinary skill in the art would understand that for low salinity secondary flooding, after the low salinity water breakthrough into production well (s) 1a-1d, the produced water contains a mixture of relic water (water originally in the oil reservoir) and low salinity water. For tertiary flooding, after water with low salinity breakthrough into the production well (s), the produced water usually contains a mixture of (a) relict water, (b) any previously injected water (for example, water with high salinity) and (c) injected water with low mineralization. Samples of the resulting water can be taken continuously or intermittently. A breakthrough of the displaced additional oil zone may occur before the low salinity water breakthrough into the well. However, due to heterogeneities in the oil reservoir, for example, the difference in the permeability of the oil-bearing layers of the formation, water with low salinity may break through into the production well (s) from one or more of the oil-bearing layers with higher permeability, before the breakthrough of the transferred zone of additional oil from one or more from oil-bearing layers with low permeability.

Information related to the breakthrough of low salinity water into the production well (s), together with information related to the presence of additional oil in oil recovered from the production well (s), allows for more efficient management of low salinity waterflooding. In this case, the development of the spread of waterflooding with low salinity can be easily determined by comparing samples of recovered oil and, optionally, recovered water, over a long period of time from one or more production wells (relative to background oil samples and recovered water). As a result, appropriate measures can be taken to control the water cut of the well, contain oil, if found, remaining in the formation after conventional production methods, and increase the life of the well.

If necessary, a marker preparation can be added to the low salinity injected water, and the recovered water is analyzed for the presence of a marker preparation indicating the breakthrough of low salinity water into the production well (s).

In the event that more than one production well is used, it is preferred that oil samples are taken from each of the production wells, and oil samples from each of the production wells are analyzed to determine the compositional signature after flooding for oxygenated organic compounds in the oil. Thus, identifying the presence or absence of compositional signatures for oxygenated organic compounds indicative of additional oil in different production wells allows tracking the spread of low salinity waterflooding, in particular by identifying areas of the oil reservoir from which additional oil has not been recovered. When there is more than one injection well and a marker formulation is added to the low salinity injection water, it is preferred that a different marker formulation is used for each production well to monitor the movement of the low salinity injection water through the oil reservoir (i.e. movement between different pairs of injection and production wells).

In addition, for tertiary waterflooding with low salinity, the monitoring of the oil-to-water (o / w) ratio in fluids produced from the production well (s) can be performed by determining the total production rate for the recovered fluids (oil, water and gas) and operating rates. for recoverable streams of oil and water, separated in production equipment. An increase in the L / W ratio indicates the arrival of the zone of transferred additional oil to one or more production wells. If possible, monitoring the L / V ratio for each production well can be done by sampling the fluids extracted from each production well.

Produced oil samples can be analyzed in production equipment, or in a laboratory remote from production equipment. Likewise, recovered water samples can be

- 18 036572 analyze in production equipment or in a laboratory remote from production equipment. To reduce the risk of any changes in the chemical composition of the samples, the samples can be cooled before analysis (for example, they can be cooled to a temperature of less than 10 ° C, in particular, to a temperature in the range from 3 to 5 ° C). The risk of any changes in the chemical composition of the samples can be further reduced by ensuring that oxygen is removed from the samples. In particular, samples can be stored under an inert atmosphere, such as nitrogen. Preferably, the produced oil samples are stored prior to analysis for less than 1 month, more preferably less than 2 weeks, in particular less than 1 week.

As discussed above, methods 200, 400 and 600 can be performed during secondary or tertiary low salinity waterflooding.

One injection well and one production well can be used, however, more than one injection well and more than one production well are preferred. There may be various spatial relationships between some or every injection well and some or every production well. The injection wells can be located around the production well. In another embodiment, the injection wells can be located in two or more rows, between each of which there are production wells. Typical onshore injection wells are in-line areal flooding, staggered areal flooding, two-spot, three-spot, four-spot, five-spot, seven-spot and nine-spot. The patterns are called normal or correct if each includes only one production well. Schemes are considered reversed if each includes only one injection well. One of ordinary skill in the art should understand how to control the operation of in-line injection wells to achieve maximum oil recovery during low salinity waterflooding.

The waterflooding contour can be changed during the production of the oil reservoir to change the direction of flow in the reservoir to ensure contact with the intact oil. It is also widely used to reduce the size of the waterflooding contour through drilling with a smaller interval (infill), which improves oil recovery by increasing the continuity of the reservoir between injection wells and production wells. This method, however, is less suitable for offshore oil reservoirs due to the high cost of infill drilling. Methods 200, 400, and 600 can be used to determine the optimal locations to drill infill wells based on the presence or absence of differences in the OOC signatures in the oil produced from existing production wells (and the extent of this difference).

The present invention will be further illustrated by the following examples.

experimental part

The following examples of experimental results help to demonstrate the change in the distinguishing characteristics of the composition of oxygenated organic compounds in mobile oil before and during waterflooding. Changes in distinguishing features may be associated with the production of additional oil.

Core flooding device.

Coreflood experiments have been performed using coreflooding equipment operating under conditions other than oil reservoir conditions (commonly referred to as simplified conditions) up to 75 ° C, 20 bar abs. and higher limiting overburden pressures up to 60 bar abs. The core flooding device uses fluids without free gas (oil and water have no dissolved gases under experimental conditions).

Core column preparation.

For the study, cores (rock samples) 3 "long and 1.5" in diameter were used. The skilled person, however, will appreciate that other core sizes can also be used. Cores were prepared either from sandstone cores taken from oil reservoirs (cores A, B, C, D, E, and I) or from an outcrop massif (cores F, G, and H). By core is meant a cylindrical section of porous reservoir rock obtained by drilling the rock with a core drill having a rotating annular cutting tool and a cylindrical core storage device. The rock properties in different layers of the core can be very different.

Porosity, water permeability (K _w ) at 100% water saturation (S _w = 1) and mineralogical composition of core samples are shown in table. 1. In the case of outcrop samples, the mineralogical composition was represented by averaged values determined by X-ray diffraction from several outcrop samples. For C and E core samples, the mineralogical composition was estimated using samples adjacent to those used in the waterflood experiments. X-ray diffraction data for core sample D were absent.

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Table 1

Breed analysis

Column type Porosity% Kw at Sw = l (millidarci, mD) Quartz,% Clay content,% Other minerals,% Kern A - St. one 24.8 190.0 94.3 3.1 2.6 Kern A - St. 2 23.8 36.0 83.1 6.9 10.0 Kern B - St. one 15.2 37.1 75.3 And, 6 13.0 Kern B - St. 2 15.1 41.8 87.1. 6.5 6,3 Kern S - St. one 24.8 91.2 69.4 20.5 Yu, 1 Kern S - St. 2 14.7 7.1 83.0 8.4 8.6 Kern D - St. one 16.0 128.2 Kern E - St. one 18.9 15.1 68.6 3.6 27.8 ' Kern D - St. 2 16.7 170.0 93.2 5.4 1.4 Kern S - St. 3 21,7 108.9 78.5 ' 14.0 7.5 Kern S - St. 4 24.7 101.2 78.5 14.0 7.5 ' Kern F - St. one 15.2 37.5 76.0 of 12.7 ' Kern G - St. one 29.4 948.2 85.0 10.9 4.1 Kern N - St. one 24.6 158.1 86.6 8.4 5.0

Column Other minerals in tab. 1 refers to other crystalline minerals besides quartz and clays, including dolomite, calcite, feldspar, siderite, plagioclase, pyrite, halite, hematite, goethite, and barite.

First, each core sample was brought to its original state, i.e., the sample was cleaned using well-miscible solvents (for example, methanol and toluene) so that the core sample was as close as possible to the state of a hydrophilic core. This cleaning continued until the liquid flowing out of the core sample became colorless. After cleaning, the core sample was placed in a hydrostatic-type core holder and saturated with relict water with high mineralization. The composition of the relict water used in each example is shown in table. 4. After passing approximately 10 pore volumes (PO) of relict water, a core sample was removed from the hydrostatic core holder and the initial water saturation was established in the core sample using the procedure described below.

Getting the initial water saturation (S _wi ).

It is important that each core sample has a characteristic initial water saturation (Swi) value. The initial water saturation of the core sample is achieved by reducing the saturation of the porous plate using nitrogen - a gas with pronounced non-wetting properties. This method is well known in the art and will not be described in detail here. After reaching the initial water saturation, the core sample was placed in a hydrostatic-type core holder and saturated with refined oil under back pressure. Then, elutriation (described below) was performed to determine the obtained Swi value.

Aging of core samples.

Then the core sample was placed in a core holder and slowly brought to the test conditions by increasing the pressure and temperature.

Further, the refined oil under test conditions was displaced by crude by injecting a column of toluene with a volume of 0.5 PO. In this case, a column of toluene was injected into the core sample before the injection of crude oil. Toluene mixes with both refined oil and crude oil, and therefore allows crude oil to easily displace refined oil. After stabilizing the pressure drop across the core sample, the effective permeability of the core sample to crude oil was determined using a method well known in the art. Next, the aging of the core sample was performed at an elevated temperature in crude oil for either one week (Examples 1-8 and 10-13) or three weeks (Example 9). During the aging process, crude oil was displaced just before the start of the core flooding. Crude oil was also replaced weekly during the aging process in Example 9. A minimum of one pore volume of crude oil was injected into the core sample and sufficient crude oil was used to achieve a constant pressure drop (differential pressure) across the core sample.

The properties of samples of crude oil used in the aging process are shown in table. 2.

table 2

Properties of crude oil samples

Raw oil Density at room temperature (g / ml) Viscosity Total acid number (mg / g KOH) Total base number (mg / g KOH) at 40 ° C (centistokes) at 100 ° C (centistokes) one 0.9155 40.5 6.8 0.42 0.39 2 * 0.9354 117.0 12.3 0.37 0.49 3 0.9171 41,7 6.8 0.23 0.52

* Crude Oil 2 was diluted with dodecane to lower the viscosity.

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Core flood tests.

All coreflood tests were performed under non-stationary conditions using procedures well known in the art.

Water was injected into the core samples with a flow rate indicated in table. 4 (corresponds to the typical rate of advance of the front during waterflooding of an oil reservoir).

Secondary flooding tests were carried out using one type of water (low salinity water). The core flood tests with low salinity secondary waters continued until an equilibrium state of pressure drop and oil production was achieved. With regard to oil production, equilibrium was determined by the absence of oil in the outlet flow from the core sample. Then the water permeability of the core sample was measured at the residual (remaining) oil saturation in a manner well known to those skilled in the art.

The tertiary flood tests were carried out with high salinity water using the secondary recovery method. High salinity secondary water core flooding tests continued until equilibrium pressure drop and oil recovery readings were reached. Then low salinity waterflooding began and continued until pressure drop and oil recovery rates reached equilibrium. And in this case, with regard to oil recovery, the achievement of equilibrium was determined by the absence of oil in the output stream withdrawn from the core sample. Then the water permeability of core samples was measured at residual (remaining) oil saturation.

The composition of the water samples used in the coreflood tests is presented in table. 3.

During the coreflood tests, samples of oil and the resulting aqueous effluent were collected and the amount of oil recovered under various waterflooding conditions was determined.

At the end of the waterflood sequence, the last oil saturation of the core sample was determined through an elutriation test (described below) to ensure an effective material balance in the waterflood sequence.

Table 3

Water composition

Water 1 Water 2 Water 3 Water 4 Water 5 Water 6 Water 7 Water 8 Water 9 Water 10 Salt mg / l mg / l mg / l mg / l mg / l mg / l mg / l mg / l mg / l mg / l N ANSO ₃ 2464.43 74.48 191.37 6.28 191.37 6.28 191.37 31.90 0.00 47.84 Na ₂ SC> 4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 CaCl ₂ .2H ₂ O ^a 260.41 7.87 1467.07 48.12 1467.07 36.34 1467.07 9581.05 6700,00 5524.05 MgCl ₂ .6H ₂ O ^a 276.03 8.34 10639.80 348.99 10639.80 163.60 10639.80 0.00 300,00 5319.90 CS1 68.64 2.07 724.57 23.77 724.57 23.77 724.57 724.57 600.00 724.57 SrCl ₂ .6H ₂ O ^a 14.30 0.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Nai 30223.25 913.35 0.00 0.00 0.00 0.00 50,000.00 50,000.00 28200,00 50,000.00 NaCl 0.00 0.00 23478.11 770.08 14086.87 462.04 3960.09 4093.80 0.00 4082.7 OSRTV (mg / l) 33090.87 1000.0 30489.72 1000.1 21098.48 596.22 60971.70 62085.16 33999.98 61520.39

^a Crystallization water is not included in the RTOS.

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Table 4

Coreflood tests

Example Column type Connate water Oil type Secondary water Tertiary water 1 Discharge rate (ml \ hour) Extra oil recovered one Kern A - pillar. one Water 1 Oil 1 Water 1 Water 2 4 Yes 2 Kern A - pillar 2 Water 1 Oil 1 Water 3 Water 4 3.9 Yes 3 Kern B - pillar. one Water 7 Oil 2 Water 3 Water 4 3.99 Yes 4 Kern A - pillar 2 Water 7 Oil 2 Water 3 Water 4 ten Yes 5 Kern C - pillar. one Water 3 Oil 2 Water 3 Water 4 ten Yes 6 Kern C - pillar 2 Water 7 Oil 2 Water 4 4 No data 7 Core D - pillar. one Water 8 Oil 2 Water 3 3.87 8 Kern E - pillar. one Water 9 Oil 2 Water 3 Water 4 3.86 Yes nine Core D - pillar 2 Water 10 Oil 3 Water 3 Water 6 3.82 Yes ten Kern C - pillar 3 Water 3 Oil 3 Water 3 Water 4 ten Yes AND Kern F - pillar. one Water 3 Oil 3 Water 4 ten No data 12 Kern G - pillar. one Water 3 Oil 3 Water 4 ten - 13 Kern N - pillar. one Water 3 Oil 3 Water 4 ten No data

Exhaustion tests.

The elutriation tests were carried out at different stages of core sample preparation and waterflooding experiments. The purpose of the elutriation test is to measure the volume of fluid within the core sample at different stages of the experiment. For example, an elutriation test performed on a core sample with 100% water saturation will provide data on the pore volume and porosity of the core sample, while an elutriation test performed on a core sample with initial water saturation (S _wi ) or residual oil saturation (Sor) will provide data on the level of these saturation values. Thus, the results of the elutriation tests give confidence in the volumetric data obtained during the flooding experiments.

In elutriation tests, the unadditive fluid in the pore space of the core sample can be mixed displacement with the additive fluid, or the additive fluid in the pore space of the core sample can be mixed displacement with the unadditive fluid. Thus, an aqueous fluid without additives can be subjected to miscible displacement with an aqueous fluid with added iodide (or vice versa), while an oily fluid without additives can be subjected to miscible displacement with an oil fluid with added iododecane (or vice versa). The oily fluid with the additive may be a refined oil with an additive. The density of the miscible displacement fluid (effluent) is determined over time by sampling the effluent. The densities of the effluent samples are normalized to the density of the additive fluid (p _sample = p _discharge / p additive _fluid ) and the normalized densities are plotted versus the volume of the effluent displaced from the core as each of the samples of the effluent is taken. The volume of fluid (aqueous or oily fluid) within the core sample is then calculated based on the volume of displaced fluid present in the effluent samples. In this case, the volume of the mobile fluid can be calculated from the known densities and volumes of each of the samples of the effluent stream.

When the elutriation test is performed on a core sample with 100% water saturation, aqueous fluids are used and the total pore volume of the core sample is obtained in the test.

When the elutriation test is carried out on a core sample with an initial water saturation S _wi , part of the pore volume of the core sample is occupied by a mobile oil phase, and the rest of the pore volume is occupied by a stationary water phase. Therefore, the elutriation test uses oil with the addition of iododecane (oil fluid) as the drive fluid. Accordingly, the volume of aqueous fluid in the pore space of a core sample at water saturation S _wi is:

Volume of aqueous fluid = Total pore volume - Volume of oil.

When the elutriation test is performed on a core sample at residual oil saturation, Sor, part of the pore volume of the core sample is occupied by the mobile water phase, and the remainder of the pore volume is occupied by the stationary oil phase. Therefore, the elutriation test uses an aqueous fluid with added iodide. Accordingly, the volume of oil in the pore space of a core sample at oil saturation Sor is:

Oil volume = Total pore volume - Volume of aqueous fluid.

Thus, provided that the total pore volume of the core sample is determined, the volume of oil remaining in the core sample can be determined.

- 22 036572

As mentioned above, during successive core floods, samples of the recovered oil and the resulting effluent were collected and the volume of oil recovered under various flooding conditions was determined.

Next, the percentages of additionally produced oil were calculated:

[(Sor - sJm S _oi -S _or )] xl00%

In this case, Soi (initial oil saturation) was calculated from the ratio:

S _oi = (pore volume of hydrocarbons) / total pore volume.

The volume of hydrocarbons in the pores was determined by elutriation tests carried out with a core sample at the initial water saturation S _w i. The total pore volume was determined during elutriation tests, when the entire pore volume of the core sample was filled with water, i.e. before the definition of S _w i.

The residual oil saturation, Sor, was then calculated based on the volume of oil recovered during the secondary flooding:

S _or ⁼ S _o j - [oil recovered from re-flooding / total pore volume].

Sor ¹ was determined using the volume of oil recovered from tertiary waterflooding:

Sor ^{1 =} S _or - [Tertiary Waterflood Oil / Total Pore Volume].

The total oil recovered was compared with the last residual oil saturation of the cores determined in the elutriation tests to confirm the effective material balance during waterflooding.

In the tertiary low salinity coreflood tests, the criterion for additional oil recovery compared to the previous high salinity secondary coreflood was taken as at least a 1.5% increase in oil recovery.

High resolution mass spectrometry.

Several oil samples from coreflood experiments were selected for further analysis using high resolution mass spectrometry (HRMS). These oil samples were diluted with an aromatic solvent such as toluene or xylene. Samples to be ionized using positive and negative electrospray ionization (ESI (+) or ESI (-)) were diluted with alcohol. Oil samples from coreflood experiments were analyzed using one or more mass spectrometric instruments (analyzers): Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), liquid chromatography-time-of-flight mass spectrometry (LC-TOF-MS), ion trap mass spectrometry (IT-MS). MCBP is a powerful and versatile method for the detailed study of the composition of crude oil. HRMS uses controlled ionization of oil sample components to generate organic ions with minimal fragmentation. The ionization methods used were ESI (+), ESI (-), APPI (+) or APPI (-).

FT-ICR-MS, HR-TOF-MS, and IT-MS measure ion mass with high precision, allowing you to match the unique chemistry of each m / z value within manually specified parameters. FT-ICR-MS has higher resolution than HR-TOF-MC and IT-MS, although all of these methods have a resolution (m / Am) of about 100,000 or more at 400 m / z.

It is possible to correlate general formulas with classes of homologous compounds or homologous series of compounds on the basis of the established chemical composition, the choice of ionization method and detailed chemical analysis of crude oil. In addition, the degree of unsaturation for each mass can be calculated from the established chemical composition by determining the equivalent mass of a prepolymer containing 1 mol of vinyl double bonds (DBE), where DBE = 1 corresponds to either one π-bond (bond C = C or C = 0 ), or one completely saturated closed ring. The corresponding structural formulas for organic compounds having DBE values from 0 to 7 are shown in table. 5a and 5b. For a specialist it should be clear that not all compounds shown in table. 5a and 5b are found in crude oil and that the crude oil may contain compounds having DBE values greater than 7.

As measuring tools for HRMS for the analysis of selected oil samples, we used 12 T Bruker SolarisX and 4.7 T Bruker SolarisX ion-cyclotron resonance Fourier transform mass spectrometers, a LECO Citis HR-TOF mass spectrometer, and a ThermoScientific mass spectrometer. Orbitrap ™ IT. For an FT-ICR mass spectrometer, samples were injected by extraction, and 200 to 300 spectra were averaged to obtain a total mass spectrum. For HR-TOF and IT mass spectrometers, samples were injected either by extraction or by analysis with the injection of a sample into the flow (FIA), i.e. with separation of the liquid chromatography column from the device. When using the HR-TOF-MS method, fewer scans were averaged to form the mass spectrum than when using the FT-ICR-MS method, for example less than 10. For the IT-MS method, less than 10 scans were averaged when the ionization was APPI technique, or about 40 scans were averaged when ESI technique was used for ionization. The HRMS measuring instruments worked with the following resolution.

Table 5 a

Corresponding structural formulas of the equivalent weight of a prepolymer containing 1 mol of vinyl double bonds (DBE) for hydrocarbons and oxygen-containing compounds

DBE Hydrocarbons Oxygenated compounds 0 one about 2 ^ 0 4 ABOUT ABOUT .he 7 About οό

- 24 036572

Table 5b

Corresponding structural formulas for the equivalent weight of a prepolymer containing 1 mol of vinyl double bonds (DBE) for nitrogen compounds and sulfur compounds

DBE Nitrogen compounds Sulfur compounds 0 one О h ₂ n S KIU 2 le 4 about nine ABOUT 7 | OQ O

FT-ICR-MS - at a maximum resolution of more than 200,000 m / Δm at 400 m / z;

HR-TOF-MS - at a maximum resolution of approximately 100,000 m / Δm at 400 m / z;

IT-MS - at a maximum resolution of over 180,000 m / .Διιι at 400 m / z.

The molecular weight cutoff for the mass spectrum obtained using FT-ICR-MS was typically in the range 1400 to 1600, for example about 1500 m / z. The molecular weight cutoff for the mass spectrum obtained using HR-TOF-MS was typically in the range 800 to 850 m / z. The molecular weight cutoff for the mass spectrum obtained using IT-MS was typically in the range of 1000 to 2000 m / z.

Next, the spectra were processed to obtain the chemical composition (the error in determining the mass was less than 5 ppm). Ions were determined in the mass spectrum in one of two ways: 1) the software of the mass spectrometer was used to determine ions falling into the following ranges of parameters: the number of elements C = 0-100, H = 0-200, N = 0-4, O = 0-5 and S = 0-3; or 2) a table of spectra was obtained from the data collected by the mass spectrometer, which was then entered into a program for analyzing the characteristics of crude oil and its products at the molecular level (Petroleum). Using this program, the data were re-calibrated and the ions were determined falling within the following parameter ranges: C = 0-100, H = 0-200, N = 0-4, O = 0-5 and S = 0-3.

To further improve the interpretation of the data, only the chemical compositions assigned to the homologous class of at least three members, for example at least five members, were used. The class of homologous compounds can be either a class of homologous hydrocarbon compounds or a class of homologous hydrocarbon compounds containing one or more heteroatoms, for example, one or more heteroatoms selected from O, N and S. Preferably, only chemical compositions assigned to homologous series within the class of homologous compounds in which the rows were defined by the range of DBE values. It should be clear to the skilled person that members of a class of compounds have the same general formula, but may differ in their structure or in their functional groups. The skilled person will also understand that the homologous series within the class of homologous compounds belong to the group of compounds that differ only in the number of CH2 groups (homologous difference) in the main carbon chain.

It will also be appreciated by the skilled person that many different classes of homologous compounds may be present in the crude oil.

The main ionization methods used to analyze oil samples by mass spectrometry methods were:

electrospray ionization of negative ions ESI (-), capable of ionizing, for example, phenols, carboxylic acids, pyrroles and pyrolidines. Classes of homologous compounds that can be found include C _x H _y O, C _x H _y O ₂ , C _x H _y O _3, and CxHyN, where x and y are integers;

electrospray ionization of positive ESI (+) ions, capable of ionizing, for example, amines and pyridines. Classes of homologous compounds that can be detected include CxHyN, CxHyNS CxHySO, CxHySO2, CxHySO3, and CxHyNO, where x and y are integers;

photoionization of positive ions at atmospheric pressure APPI (+), capable of ionizing aromatic hydrocarbons, phenols, pyrroles and pyridines, and sulfur-containing hydrocarbons, such as thiophenes. Classes of homologous compounds which may be detected include C _x H _{y C x H y S, C x} H y S _2, and CxHy CxHyN, where x and y - are integers;

photoionization of negative ions at atmospheric pressure APPI (-), capable of ionizing aromatic hydrocarbons, phenols, pyrroles, acids and sulfur-containing hydrocarbons. Classes of homologous compounds that can be found include C _x H _y CxHyS, CxH _y S ₂ , CxHyO, C _x H _y O _2, and CxHyN, where x and y are integers.

Before ionization, oil samples are further diluted to a concentration in the range of 0.1 to 1 mg / ml in a solvent or solvent mixture. Examples of solvents and mixtures of solvents that can be used in various ionization methods are given in table. 6.

Table 6

Solvents

Ionization method Suitable solvents or solvent mixtures APP1 (+) toluene xylene: toluene (6: 4 by volume) APPI (-) toluene xylene: toluene (6: 4 by volume) ESI (+) toluene: propan-2-ol (1: 2 by volume) + 1 vol% acetic acid (174 mmol) toluene: methanol (1: 2 by volume) toluene: methanol (6: 4 by volume) + 0.1 vol.% formic acid (26.0 millimol) xylene: methanol (6: 4 by volume) + 0.1 vol% formic acid (26.0 millimol) ESI (-) dichloromethane: methanol (1: 2 by volume) toluene: methanol (1: 5 v / v) + 0.1 vol% ammonium hydroxide (8.5 mmol) toluene: methanol (6: 4 by volume) + 0.1 vol% ammonium hydroxide (8.5 mmol) xylene: methanol (6: 4 by volume) + 0.1 vol% ammonium hydroxide (8.5 mmol)

The intensities of the peaks in the spectrum corresponding to individual ions (which are markers of additional oil released during low salinity waterflooding) were normalized to the total intensity of a widespread and stable class of homologous organic compounds, which compensated for any intensity variations caused by fluctuations during

- 26 036572 ionization. The resulting normalized intensities will hereinafter be referred to as the primary normalized intensity data.

Preferably, the stable class of homologous compounds used for standardization has a certain DBE number and a certain hydrogen deficiency (HD) number, also referred to as the hydrogen deficiency index. Hydrogen deficiency numbers for organic compounds can be easily calculated by the skilled person. For example, the hydrogen deficiency numbers for benzene (C6H6) and cyclohexane (C6H12) are -6 and 0, respectively.

The class of homologous compounds used for standardization should be present in all oil samples obtained from a core sample during individual waterflooding. The stability of the intensities of the selected class of homologous compounds means that this class of homologous compounds does not serve as a marker for additional oil released during low salinity waterflooding. Normalization of the peak intensities in the spectra makes it possible to compare the intensities in the mass spectra, performed on oil samples obtained from the core sample during each waterflood, and to compare the abundance of various individual compounds, classes of homologous compounds or homologous series of compounds in the mass spectra for each of the samples. oil. The classes of homologous compounds used for the primary standardization for the ionization methods used in each example are presented in table. 7.

The intensities of individual peaks in the mass spectra were normalized using the following ratio:

Full anti-skins x 1000

YUIIIMZH SiMJgHSKBWCM * = —-------------------------------------—

LC1ZHYA V # # lttffli GC # for a cassock

The total intensity of an individual ion is multiplied by 1000 for ease of reference.

The total intensity of an individual ion is determined from the intensity of the peak attributed to the monoisotopic form of an individual ion, i.e. ion containing only the basic or most common isotopes for each element of its molecular formula (for example, isotopes 1H, ¹² C, ¹⁴ N, ¹⁶ O or ³² S). The total intensity of an individual ion is then calculated from the intensity of the monoisotopic ion by accounting for ions containing one or more of the less common isotopes H, C, N, O, and S. The mass and abundance of these isotopes is given below:

Mass Prevalence

2H 2.014101778 0.000115 13C 13.00335484 0.0107 15N 15,0001089 0.00364 170 16.9991317 3.80Е-04 180 17.999161 2.05E-03 33S 32.97145876 0.0076 34S 33.9678669 0.0429 36S 35.96708076 2.00E-04

To calculate the total intensity for all isotopic forms of an individual ion from the intensity of the monoisotopic ion, the following calculations are performed:

Total intensity of an individual ion = monoisotopic intensity x (1+ (abundance 2H x number of hydrogen atoms in a molecular ion) + (abundance 13C x number of carbon atoms in a molecular ion) + (abundance 15N x number of nitrogen atoms in a molecular ion) + (abundance 170 x number of oxygen atoms in a molecular ion) + (abundance 180 x number of oxygen atoms in a molecular ion) + (abundance 33S x number of sulfur atoms in a molecular ion) + (abundance 34S x number of sulfur atoms in a molecular ion) + (abundance 36S x number sulfur atoms in a molecular ion)).

For example, for a molecular ion with the molecular formula C9H8O1 having a monoisotopic intensity equal to 425S8, the total intensity of the molecular ion is determined as follows:

The total total intensity for the normalized series is the sum of all the total intensities of individual ions in the homologous series (within the class of compounds) of the normalized series.

- 27 036572

Table 7

Examples of classes of homologous compounds used for primary normalization for different ionization methods

ESI (+) ESI (-) APPI (+) APPI (-) Example Series used for normalization HD DBE Series used for normalization HD DBE Series used for normalization HD DBE Series used for normalization HD DBE one C _X H _V N -21 12 C _X H _V Glad -16 nine 2 C _X H _V N -21 12 C _X H _V N Happy -25 14 3 C _X H _V N -17 ten C _X H _V N -17 ten C _X H _V Glad -14 8 4 C _X H _V N -17 ten C _X H _V N -21 12 C _X H _V Glad -16 nine 5 C _X H _V N -eleven 7 C _X H _V N -21 12 6 C _X H _V N -13 8 C _X H _V N -15 nine 7 C _X H _V N -13 8 C _X H _V N -15 nine C _X H _V Glad -16 nine C _X H _V Glad -16 nine 8 C _X H _V N -13 8 C _X H _V N -21 12 C _X H _V Glad -16 nine C _X H _V Glad -16 nine nine C _X H _V N -13 8 C _X H _V N -15 nine ten C _X H _V N -13 8 C _X H _V N -15 nine AND C _X H _V N -13 8 C _X H _V N -15 nine 12 C _X H _V N -13 8 C _X H _V N -15 nine 13 C _X H _V N -13 8 C _X H _V N -15 nine

ESI (+) - all molecular ions are protonated.

ESI (-) - all molecular ions are deprotonated.

Glad - molecular ions are radical ions.

Further, the normalized intensities of individual ions are subjected to the following normalization (secondary normalization), in which the total intensity of a class of homologous compounds or homologous series of compounds is determined and multiplied by 1000 (to obtain the total total intensity). The secondary normalized intensity data is then obtained by determining the ratio of the total total intensity for a class of homologous compounds or homologous series of compounds for oil samples obtained during low salinity waterflooding to the total total intensity for the same class of homologous compounds or homologous series of compounds for a background oil sample. ... Typically, for a re-core flood test, a background oil sample is drawn from the core sample, at the beginning or shortly after the start of the core flood test (i.e., it is an oil sample that would not interact with the low salinity injected water). Typically, for a tertiary low salinity coreflood test, a background oil sample is retrieved during a previous high salinity core flood test. Typically, oil samples were selected for mass spectral analysis to investigate potential markers for additional oil in secondary or tertiary core flooding tests with low salinity during the time interval when an increased amount of oil was observed in the effluent from the core sample. In the secondary coreflood test, this usually occurred after the breakthrough of low salinity water (also called brackish water).

The normalized intensity data for Examples 1-13 are presented in table. 8.

Table 8 __________ Secondary normalized rates of oil samples __________________

Average but emitted rates of oil samples The number of analyzed oil samples and average intensities C _x H _y N (ESI (+)) C _x H _y O ₂ (ESI (-)) С _x Н _у О ₂ (ESI (-)) DBE = 1 Secondary core flooding averaging Averaging over tertiary coreflooding Secondary core flooding averaging Averaging over tertiary coreflooding Secondary core flooding averaging Averaging over tertiary coreflooding During the secondary core flooding During tertiary coreflooding one hundred 100.36 - - - - one 2 one hundred 104.11 - - - - one 2 one hundred 105.1 one hundred 108.58 one hundred 213.63 one 5 one hundred 100.43 one hundred 131.86 one hundred 169.39 one 7 98.48 90.23 158.12 309.55 150.72 223.68 5 8 118.97 - 200.95 - 920.58 - 33 99.61 - 121.14 - 156.8 - 6 No data 104.01 130.81 95.22 171.53 99.05 373.64 5 15 96.24 106.34 289.52 359.65 426.21 972.05 7 eighteen 103.09 111.26 99.43 171.86 191.73 505.12 8 98.68 - 149.62 - 162.28 - eighteen No data 101.04 - 124.73 - 140.06 - 24 No data 97.35 - 126.52 - 106.22 - 16 No data

Examples 1 and 2 include secondary core floods with High Salinity Waters 1 and 3, respectively, and tertiary core floods with Low salinity Waters 2 and 4, respectively. Oil samples recovered from these waterflooding tests were analyzed only by means

- 28 036572

ESI-MS. Comparison of the average normalized intensity data for the CxHyN class of homologous compounds for oil samples obtained for secondary and tertiary waterflooding (i.e. for the entire coreflood test) showed that the average normalized intensities did not change significantly, which indicates that The CxHyN class of homologous compounds does not serve as a marker for additional oil produced during tertiary low salinity waterflooding.

Example 3 relates to a secondary coreflood with high salinity with Water 3 and tertiary coreflood with low salinity with water 4.In Example 3, ESI-MS positive ion analysis of oil samples recovered during secondary and tertiary coreflooding showed that C _x H _y N homologous class remains stable throughout the coreflood test. ESI-MS negative ion analysis of oil samples revealed a slight increase in the normalized CxH intensity of _the O ₂ homologous compound for oil samples recovered during low salinity tertiary waterflooding, when summed over all identified DBE values (when compared to oil samples recovered in time of secondary flooding of cores with high salinity). The extraction of averaged normalized intensity data for C _x H _y O ₂ class compounds with DBE = 1 showed a stronger increase in the normalized intensity for oil samples recovered during tertiary waterflooding with low salinity (when compared with oil samples recovered during secondary waterflooding with high mineralization). The C _x H _y O ₂ class of homologous compounds can therefore serve as a marker for additional oil released during tertiary waterflooding with low salinity Water 4.

Examples 4 and 5 correspond to core flooding tests using the same waters as in Example 3. The same conclusions can be drawn as in Example 3, i.e. that the CxHyN class of homologous compounds remains stable in oil samples recovered during the entire waterflooding, while there is an increase in the concentration of CxHyO2 class of homologous compounds (for all identified values of DBE and DBE = 1) for oil samples recovered during tertiary waterflooding with low salinity (when compared to a sample of oil recovered during secondary flooding with high salinity). Although the variations in the intensities of the C _x H _y N class of homologues for Example 5 are higher than for Examples 1 and 4, these variations are significantly lower than the variations in intensities for the C _x H _y O ₂ class of homologous compounds for all identified DBE values and for DBE = 1.

Example 6 presents normalized intensity data for secondary waterflooding with low salinity with Water 4. Average normalized intensity data were obtained by normalizing to an oil sample obtained previously from core floods (i.e. oil displaced from a portion of a core column to be subjected to further filling with water with low salinity). The normalized intensity for the CxHyN class of homologous compounds identified by positive ion ESI-MS analysis was 118.97, similar to the values obtained for oil samples recovered during tertiary low salinity core floods from Examples 1-5. The normalized intensities for the CxHyO2 class of homologous compounds identified using negative ion ESI-MS analysis had an average of 200.95 (across all DBEs) and 920.58 (for DBE = 1), indicating that CxH _on O ₂ the homologous class also acts as a marker for additional oil released during low salinity re-flooding.

Example 7 illustrates normalized rate data for low salinity secondary waterflooding with Water 3. Average normalized rate data was obtained by normalizing against a previously flooded oil sample (recovered from a portion of the core to be further flooded with high salinity water). With regard to the previous examples, the average normalized intensity for the CxHyN class of homologous compounds was about 100 (99.61). The average normalized intensities for the CxHyO2 class of homologous compounds for all identified DBE values (121.14) and for DBE = 1 (156.8), were significantly lower than those observed in the secondary flooding tests with low salinity core in Example 6, which indicates that that high salinity water is not as effective as low salinity water for releasing homologous compounds of this class.

Example 8 presents the normalized intensity data for the Water 3 secondary coreflood and low salinity water 4 tertiary coreflood tests. This example used the same waters as Example 5 and obtained similar results.

Example 9 relates to secondary coreflood with Water 3 with high salinity and tertiary core flooding with Water 6 with low salinity. It was found that the average normalized intensity for the CxHyN homologous class remained unchanged for oil samples recovered during the entire flood test, while there was a marked increase in the average normalized intensity for the CxHyO2 homologous class for oil samples recovered during tertiary waterflooding. low salinity core for all identified DBE values and for DBE = 1 (versus oil samples recovered during secondary flooding of high salinity cores).

- 29 036572

Example 10 relates to secondary coreflooding with high salinity water and tertiary coreflooding with low salinity water (same waters used in Example 5). It was found that the average normalized intensity for the C _x H _y N class of homologous compounds remained unchanged for oil samples extracted during the test on flooding, while there was a noticeable increase in the average normalized intensity for ShN _y O ₂ class of homologous compounds sample of oil recovered during tertiary low salinity coreflooding for all identified DBE values and for DBE = 1 (versus oil samples recovered during high salinity secondary coreflooding).

Examples 11-13 are similar to Example 6 (secondary core flooding with low salinity with Water 4). The same conclusions can be drawn as for Example 6.

FT-ICR-MS data for Coreflood Experiment 3 (using ESI (-) as ionization method).

Example 3 relates to a tertiary low salinity coreflood test with Water 3, followed by a secondary high salinity coreflood test (Water 4).

FIG. 7 is a graph showing carbon number (molecular size) versus equivalent weight of a prepolymer containing one mole of vinyl double bonds (DBE) for the CxH _y O ₂ homologous class of oil samples recovered during Coreflood Experiment 1. Dot size and gray scale correspond to signal intensities. The plot for oil sampled from an oil reservoir (Sample 0) is the background distribution of the carbon number versus DBE for CxH _y O ₂ class of homologous compounds. Sample 1 was recovered during the aging of the core sample and before all floods. It can be seen that oil during aging is significantly depleted in CxH _y O ₂ compounds with a high DBE number. Sample 2 was obtained during a secondary flooding with high salinity. It can be seen that the plot for Sample 2 resembles that for oil sampled from an oil reservoir (Sample 0). Sample 3 was recovered from a low salinity water breakthrough during a tertiary low salinity waterflood and the plot for this sample shows that the oil is enriched in compounds with a low DBE number. Sample 4 represents oil recovered later during a tertiary low salinity waterflood and the plot resembles that of sample 3 oil taken immediately after the low salinity water breakthrough. The plot for Sample 4 shows that additional C, H _y O ₂ homologous compounds were released from the porous reservoir later during the low salinity waterflooding.

HR-TOF-MS data for Coreflood Experiment 3 (using ESI (-) as ionization method).

FIG. 8 is a graph showing the carbon number (molecule size) versus the equivalent weight of a 1 mol vinyl double bond (DBE) prepolymer for the CxH _y O ₂ homologous class of oil samples recovered during Coreflood Experiment 3. Here, too, the size of the dots and shades of gray correspond to the signal intensities. The data obtained using the LC-TOF-MS method shows a pattern similar to the data obtained using the FT-ICR-MS method.

FIG. 9 shows the carbon number (molecule size) for CxH _in O _{2 of the} class of homologous compounds with DBE = 1 for Samples 0, 1, 2, 3, 4, 5, 6, and 7. It can be seen that Samples 4 and 6 taken after breakthrough of water with low salinity, enriched in homologous compounds of the class C _x H _y O ₂ (compare with background Sample 0). This indicates that FT-ICR-MS results are reproduced with LC-TOF-MS with poorer resolution.

Finally, the results presented in table. 8 and FIG. 7-9 show that additional oil can be detected by analyzing oil samples for compositional signature after flooding for oxygenated organic compounds in oil. Additional oil is considered to be detected when an identifiable difference is made between one or more of the post-flood compositional signatures for oxygenated organic compounds in the oil and the background compositional signature for the oxygenate compounds.

In addition, these results indicate that these differences may be present for many core, oil and water types.

The embodiments described above should be taken as specific examples illustrating the invention. Other embodiments of the invention can be envisioned. It should be understood that any feature described in connection with any embodiment may be used individually or in combination with other described features, and may also be used in combination with one or more features of any other of the embodiments, or any combination of any other of the execution options. In addition, equivalents and modifications not described above can also be used without departing from the scope of the invention as defined by the appended claims.

Claims (17)

CLAIM 1. A method for detecting the production of additional oil from an oil-bearing formation through which at least one injection well and at least one production well pass, during which a background oil sample is taken and analyzed to establish the background distinctive features of the composition for oxygen-containing organic compounds in oil ; start low salinity waterflooding by injecting low salinity water into the formation through an injection well; extract oil from the production well; taking oil samples after waterflooding, produced from the production well, for a long time; analyzing oil samples after waterflooding to establish distinctive compositional characteristics for oxygen-containing organic compounds in oil after waterflooding; identifying the difference between one or more of the post-flood oxygenated organic composition signatures and the background compositional signatures for the oxygenated organic compounds in the oil, characteristic of the additional oil released by the low salinity flooding. 2. The method of claim 1, wherein the compositional signature of the post-flood oil samples is compared to a background mobile oil sample. 3. The method of claim 2, wherein low salinity water is injected into the oil reservoir in a secondary recovery method. 4. A method for detecting the production of additional oil from an oil-bearing formation containing several layers of formation rock through which at least one injection well, at least one production well and at least one observation well located between the injection well and the production well passes, when the implementation of which the logging equipment is introduced into the observation well; water with low salinity is injected into the oil-bearing formation through the injection well and oil is extracted from the production well; using the logging equipment for a long time to determine the time interval t ₁ between the start of the injection of water with low salinity into the oil reservoir through the injection well (s) and the detection of a front of water with low salinity in the observation well; determining the distance L1 between the injection well (s) and the observation well and calculating the speed v, with which the water front with low salinity propagates through the oil reservoir, and v = L1 / t1; determining the distance L ₂ between the observation well and the production well (s) and using the front propagation velocity v to predict the time t ₂ when the low salinity water will break into the production well, where t ₂ = t1 + L ₂ / v; taking a background oil sample from the oil reservoir before the injection of water with low salinity and analyzing the background oil sample to establish the distinguishing features of the composition for oxygen-containing organic compounds in the oil; taking oil samples after waterflooding, produced from the production well (s), for an extended period of time and analyzing these oil samples to establish compositional distinctions for oxygenated organic compounds in oil after waterflooding to identify differences between one or more compositional characteristics for oxygenated organic compounds in oil after waterflooding and background compositional signatures for oxygenated organic compounds in oil, characteristic of additional oil released by low salinity waterflooding; increase the sampling frequency of the produced oil after waterflooding as the predicted time t _{2 for the} breakthrough of low salinity injected water into the production well approaches and exploits the identified difference between compositional signatures for oxygenated organic compounds in oil after waterflooding and background compositional characteristics for oxygenated organic compounds in oil to determine the point in time when additional oil will break into the production well. 5. The method according to any of the preceding claims, in which the oil samples are analyzed using high-resolution mass spectrometry (HRMS) to increase the total signal intensity for a class of homologous compounds with the general formula C _x H _y On (I), where x is an integer a number in the range from 5 to 100, preferably from 8 to 75, more preferably from 8 to 60, in particular from 10 to 45, y is an integer <2x + 2 and n is an integer in the range from 1 to 10, preferably 1 to 5, more preferably 1 to 3, in particular 2. - 31 036572 6. The method according to claim 5, wherein the oil samples are further analyzed by HRMS for a decrease in the intensity of the weighted average equivalent weight of the prepolymer containing 1 mol of vinyl double bonds (DBE) for the class of homologous compounds with general formula (I). 7. The method of claim 6, wherein the oil samples are further analyzed by HRMS to increase the overall signal intensity for a class of homologous compounds with general formula (I) having a DBE of 1. 8. A method according to any one of the preceding claims, wherein the produced water samples taken after the start of low salinity waterflooding are analyzed for an increase in the concentration of ions selected from Fe ²⁺ , Ca ²⁺ , Mg ² 'and Sr ²⁺ relative to the background sample produced water sampled before the start of waterflooding with low salinity. 9. The method of claim 8, wherein the produced water samples are analyzed for a decrease in total dissolved solids relative to a background produced water sample taken prior to the start of the low salinity waterflood. 10. The method according to any of the preceding paragraphs, in which register the points in time when each of the oil samples after waterflooding is produced from the production well (s); determining post-flood samples that demonstrate a difference between post-flood compositional signature and background compositional signatures for oxygenated organic compounds that are characteristic of additional oil released by low salinity waterflooding; and taking the earliest production time when a difference in post-flood sample composition is detected as the time point for additional oil to break through into the production well (s). 11. A method of inversely adapting a low salinity oil reservoir model to oil reservoir measurement data, in which additional oil is detected by the method of claim 10 to thereby obtain the production time (s) when additional oil breaks into the production well (s), as the first measurement data of the oil reservoir; obtaining additional measurement data of the oil reservoir, including the measured volume (we) of oil produced from the production well (s) during waterflooding with low salinity, as a function of time; Entering common and low salinity inputs into a low salinity oil reservoir modeling to simulate low salinity waterflooding, with the general and low salinity inputs having associated uncertainties; simulating the low salinity oil reservoir using the common and low salinity inputs to generate low salinity outputs containing the calculated point (s) in time when additional oil breaks into the production well (s); and the calculated volume (s) of oil produced from the production well (s) in low salinity conditions, as a function of time; and generating an inversely adapted oil reservoir model for low salinity waterflooding by back-matching the low salinity output to the oil reservoir measurement by adjusting uncertainties in the low salinity input. 12. The method of claim 11, wherein the additional measurement data of the oil reservoir further includes one or more of the measured volume (s) of low salinity water injected into the injection well (s) as a function of time; the measured volume (s) of water produced from the production well (s), as a function of time; measured salinity of produced water as a function of time; measured concentrations of selected ions in produced water as a function of time; measured borehole pressures in the injection well (s) and production well (s) at the depth of the oil-bearing layer (s) of the formation, as a function of time. 13. A method according to claim 11 or 12, wherein the inversely adapted oil reservoir model is used in a predictive manner to estimate the increase in future production of additional oil from the oil reservoir due to low salinity waterflooding and / or to plan for improved management of low salinity waterflooding. ... 14. A method according to any one of claims 11, 12, wherein the back-adaptation of the oil reservoir simulation is repeated one or more times during the low salinity waterflooding of the oil reservoir. 15. A method for estimating the volume of additional oil produced from an oil reservoir as a function of time, during which a reverse adaptation of a low salinity oil reservoir model to reservoir measurement data is performed by the method according to any one of claims 11-14, and when generating a back adapted - 32 036572 oil reservoir models adjust uncertainties in general inputs and in low salinity inputs; inputting high salinity input data into a back-adapted oil reservoir simulator to simulate high salinity waterflooding; controlling the operation of the inversely adapted oil reservoir program using the common and high salinity inputs to generate high salinity outputs including the calculated volume (s) of oil produced from the production well (s) in high salinity conditions as a function of time; and estimating the volume of additional oil by subtracting the calculated volume (s) of oil produced from the production well (s) in high salinity conditions as a function of time from the measured volume (s) of oil produced from the production well (s) during the low mineralization of an oil reservoir as a function of time. 16. A method for estimating an extended dewatered oil recovery period for low salinity secondary flooding, in which the volume of additional oil produced from the oil reservoir is estimated as a function of time by the method of claim 15, wherein the high salinity output further includes the calculated moment (you ) the time when water of high salinity breaks into the production well (s); and estimating the extended recovery period of dewatered oil for low salinity secondary flooding by subtracting the calculated time (s) when the high salinity water breaks into the production well (s) from the measured time (s) when the low salinity water breaks into the production well (s). well (s). 17. A method for estimating an extended period of reduced water cut of a well production for tertiary flooding with low salinity, in which the volume of additional oil produced from an oil reservoir is estimated as a function of time, by the method of claim 15, wherein the output of high salinity further includes the calculated water cut ( i) fluids produced from the production well (s); and estimating the extended period of reduced water cut for tertiary low salinity waterflooding by subtracting the calculated water cut (s) of fluids produced from the production well (s) from the measured water cut (s) of fluids produced from the production well (s) during the tertiary low salinity flooding ...